{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import geopandas\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Case study - Conflict mapping: mining sites in eastern DR Congo\n",
    "\n",
    "In this case study, we will explore a dataset on artisanal mining sites located in eastern DR Congo.\n",
    "\n",
    "**Note**: this tutorial is meant as a hands-on session, and most code examples are provided as exercises to be filled in. I highly recommend actually trying to do this yourself, but if you want to follow the solved tutorial, you can find this in the `_solved` directory.\n",
    "\n",
    "---\n",
    "\n",
    "#### Background\n",
    "\n",
    "[IPIS](http://ipisresearch.be/), the International Peace Information Service, manages a database on mining site visits in eastern DR Congo: http://ipisresearch.be/home/conflict-mapping/maps/open-data/\n",
    "\n",
    "Since  2009, IPIS has visited artisanal mining sites in the region during various data collection campaigns. As part of these campaigns, surveyor teams visit mining sites in the field, meet with miners and complete predefined questionnaires. These contain questions about the mining site, the minerals mined at the site and the armed groups possibly present at the site.\n",
    "\n",
    "Some additional links:\n",
    "\n",
    "* Tutorial on the same data using R from IPIS (but without geospatial aspect): http://ipisresearch.be/home/conflict-mapping/maps/open-data/open-data-tutorial/\n",
    "* Interactive web app using the same data: http://www.ipisresearch.be/mapping/webmapping/drcongo/v5/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Importing and exploring the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The mining site visit data\n",
    "\n",
    "IPIS provides a WFS server to access the data. We can send a query to this server to download the data, and load the result into a geopandas GeoDataFrame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import json\n",
    "\n",
    "wfs_url = \"http://geo.ipisresearch.be/geoserver/public/ows\"\n",
    "params = dict(service='WFS', version='1.0.0', request='GetFeature',\n",
    "              typeName='public:cod_mines_curated_all_opendata_p_ipis', outputFormat='json')\n",
    "\n",
    "r = requests.get(wfs_url, params=params)\n",
    "data_features = json.loads(r.content.decode('UTF-8'))\n",
    "data_visits = geopandas.GeoDataFrame.from_features(data_features, crs={'init': 'epsg:4326'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, the data is also provided in the tutorial materials as a GeoJSON file, so it is certainly available during the tutorial."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Read the GeoJSON file `data/cod_mines_curated_all_opendata_p_ipis.geojson` using geopandas, and call the result `data_visits`.</li>\n",
    "  <li>Inspect the first 5 rows, and check the number of observations</li>\n",
    " </ul> \n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "data_visits = geopandas.read_file(\"data/cod_mines_curated_all_opendata_p_ipis.geojson\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>vid</th>\n",
       "      <th>source</th>\n",
       "      <th>project</th>\n",
       "      <th>pcode</th>\n",
       "      <th>name</th>\n",
       "      <th>visit_date</th>\n",
       "      <th>visit_onsite</th>\n",
       "      <th>visit_onsite_novisitreason</th>\n",
       "      <th>longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>digging_armed_group2</th>\n",
       "      <th>forced_labour_armed_group2</th>\n",
       "      <th>pillaging_armed_group2</th>\n",
       "      <th>state_service1</th>\n",
       "      <th>state_service2</th>\n",
       "      <th>state_service3</th>\n",
       "      <th>state_service4</th>\n",
       "      <th>itsci</th>\n",
       "      <th>qualification</th>\n",
       "      <th>geometry</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>cod_mines_curated_all_opendata_p_ipis.fid-11f0...</td>\n",
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       "      <td>IPIS - 2009</td>\n",
       "      <td>codmine00191</td>\n",
       "      <td>Eohe</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>28.712580</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (28.71258 0.33188)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>cod_mines_curated_all_opendata_p_ipis.fid-11f0...</td>\n",
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       "      <td>IPIS - Ministère des Mines</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>codmine00192</td>\n",
       "      <td>Eita</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>28.699160</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (28.69916 0.32153)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>cod_mines_curated_all_opendata_p_ipis.fid-11f0...</td>\n",
       "      <td>3</td>\n",
       "      <td>IPIS - Ministère des Mines</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>codmine00242</td>\n",
       "      <td>Mungu Iko</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>28.185142</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (28.1851423 0.54499175)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>cod_mines_curated_all_opendata_p_ipis.fid-11f0...</td>\n",
       "      <td>4</td>\n",
       "      <td>IPIS - Ministère des Mines</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>codmine00260</td>\n",
       "      <td>Kiviri/Tayna</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>28.884528</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (28.884528 -0.352529)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>cod_mines_curated_all_opendata_p_ipis.fid-11f0...</td>\n",
       "      <td>5</td>\n",
       "      <td>IPIS - Ministère des Mines</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>codmine00272</td>\n",
       "      <td>Makanga</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>28.903945</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (28.903945 -0.036707)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  id  vid  \\\n",
       "0  cod_mines_curated_all_opendata_p_ipis.fid-11f0...    1   \n",
       "1  cod_mines_curated_all_opendata_p_ipis.fid-11f0...    2   \n",
       "2  cod_mines_curated_all_opendata_p_ipis.fid-11f0...    3   \n",
       "3  cod_mines_curated_all_opendata_p_ipis.fid-11f0...    4   \n",
       "4  cod_mines_curated_all_opendata_p_ipis.fid-11f0...    5   \n",
       "\n",
       "                       source      project         pcode          name  \\\n",
       "0  IPIS - Ministère des Mines  IPIS - 2009  codmine00191          Eohe   \n",
       "1  IPIS - Ministère des Mines  IPIS - 2009  codmine00192          Eita   \n",
       "2  IPIS - Ministère des Mines  IPIS - 2009  codmine00242     Mungu Iko   \n",
       "3  IPIS - Ministère des Mines  IPIS - 2009  codmine00260  Kiviri/Tayna   \n",
       "4  IPIS - Ministère des Mines  IPIS - 2009  codmine00272       Makanga   \n",
       "\n",
       "    visit_date  visit_onsite visit_onsite_novisitreason  longitude  \\\n",
       "0  2009-01-01Z             1                       None  28.712580   \n",
       "1  2009-01-01Z             1                       None  28.699160   \n",
       "2  2009-01-01Z             1                       None  28.185142   \n",
       "3  2009-01-01Z             1                       None  28.884528   \n",
       "4  2009-01-01Z             1                       None  28.903945   \n",
       "\n",
       "               ...                digging_armed_group2  \\\n",
       "0              ...                                 NaN   \n",
       "1              ...                                 NaN   \n",
       "2              ...                                 NaN   \n",
       "3              ...                                 NaN   \n",
       "4              ...                                 NaN   \n",
       "\n",
       "  forced_labour_armed_group2 pillaging_armed_group2 state_service1  \\\n",
       "0                        NaN                    NaN           None   \n",
       "1                        NaN                    NaN           None   \n",
       "2                        NaN                    NaN           None   \n",
       "3                        NaN                    NaN           None   \n",
       "4                        NaN                    NaN           None   \n",
       "\n",
       "  state_service2 state_service3 state_service4 itsci  qualification  \\\n",
       "0           None           None           None  None           None   \n",
       "1           None           None           None  None           None   \n",
       "2           None           None           None  None           None   \n",
       "3           None           None           None  None           None   \n",
       "4           None           None           None  None           None   \n",
       "\n",
       "                        geometry  \n",
       "0       POINT (28.71258 0.33188)  \n",
       "1       POINT (28.69916 0.32153)  \n",
       "2  POINT (28.1851423 0.54499175)  \n",
       "3    POINT (28.884528 -0.352529)  \n",
       "4    POINT (28.903945 -0.036707)  \n",
       "\n",
       "[5 rows x 62 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_visits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3687"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data_visits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The provided dataset contains a lot of information, much more than we are going to use in this tutorial. Therefore, we will select a subset of the column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_visits = data_visits[['vid', 'project', 'visit_date', 'name', 'pcode', 'workers_numb', 'interference', 'armed_group1', 'mineral1', 'geometry']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vid</th>\n",
       "      <th>project</th>\n",
       "      <th>visit_date</th>\n",
       "      <th>name</th>\n",
       "      <th>pcode</th>\n",
       "      <th>workers_numb</th>\n",
       "      <th>interference</th>\n",
       "      <th>armed_group1</th>\n",
       "      <th>mineral1</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>Eohe</td>\n",
       "      <td>codmine00191</td>\n",
       "      <td>300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (28.71258 0.33188)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>Eita</td>\n",
       "      <td>codmine00192</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (28.69916 0.32153)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>Mungu Iko</td>\n",
       "      <td>codmine00242</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FARDC</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (28.1851423 0.54499175)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>Kiviri/Tayna</td>\n",
       "      <td>codmine00260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FDLR</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (28.884528 -0.352529)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>Makanga</td>\n",
       "      <td>codmine00272</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FDLR</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (28.903945 -0.036707)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   vid      project   visit_date          name         pcode  workers_numb  \\\n",
       "0    1  IPIS - 2009  2009-01-01Z          Eohe  codmine00191         300.0   \n",
       "1    2  IPIS - 2009  2009-01-01Z          Eita  codmine00192         110.0   \n",
       "2    3  IPIS - 2009  2009-01-01Z     Mungu Iko  codmine00242           NaN   \n",
       "3    4  IPIS - 2009  2009-01-01Z  Kiviri/Tayna  codmine00260           NaN   \n",
       "4    5  IPIS - 2009  2009-01-01Z       Makanga  codmine00272           NaN   \n",
       "\n",
       "   interference armed_group1 mineral1                       geometry  \n",
       "0           NaN         None       Or       POINT (28.71258 0.33188)  \n",
       "1           NaN         None       Or       POINT (28.69916 0.32153)  \n",
       "2           NaN        FARDC       Or  POINT (28.1851423 0.54499175)  \n",
       "3           NaN         FDLR       Or    POINT (28.884528 -0.352529)  \n",
       "4           NaN         FDLR       Or    POINT (28.903945 -0.036707)  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_visits.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before starting the actual geospatial tutorial, we will use some more advanced pandas queries to construct a subset of the data that we will use further on: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Take only the data of visits by IPIS\n",
    "data_ipis = data_visits[data_visits['project'].str.contains('IPIS') & (data_visits['workers_numb'] > 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For those mining sites that were visited multiple times, take only the last visit\n",
    "data_ipis_lastvisit = data_ipis.sort_values('visit_date').groupby('pcode', as_index=False).last()\n",
    "data = geopandas.GeoDataFrame(data_ipis_lastvisit, crs=data_visits.crs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data on protected areas in the same region\n",
    "\n",
    "Next to the mining site data, we are also going to use a dataset on protected areas (national parks) in Congo. This dataset was downloaded from http://www.wri.org/our-work/project/congo-basin-forests/democratic-republic-congo#project-tabs and included in the tutorial repository: `data/cod_conservation.zip`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Extract the `data/cod_conservation.zip` archive, and read the shapefile contained in it. Assign the resulting GeoDataFrame to a variable named `protected_areas`.</li>\n",
    "  <li>Quickly plot the GeoDataFrame.</li>\n",
    " </ul> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "protected_areas = geopandas.read_file(\"data/Conservation/RDC_aire_protegee_2013.shp\")\n",
    "# or to read it directly from the zip file:\n",
    "# protected_areas = geopandas.read_file(\"/Conservation\", vfs=\"zip://./data/cod_conservation.zip\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "clear_cell": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd7294d8128>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ytb+cu97a2GP7vNK6PvnhTnYW1WKxOR91rT1YweJ1h50e81Xc+Vu6ApislJoK\n7AEedDi2Tyk13Xjd5mB/DrvEWY7xOsewPwB8rpTKAT43PoNddbut7S3G+YhIHPAIdh3IWcAjbUFP\n05G7548lOco+l2ES+Om8bC971JHLZ6b1OPyqbbJwx5sbeGP1oQ72eeOSWP6zU7h4umvDwYjgAJ7/\n8Uyiw3qfjH7uyzwuePZbFv19Nde8tKbX9msOVGDrJmh4msMVDd0eUwp+/cG29goUjhwqr+dIVdfe\nurdxWwBTSn1qCGsArMIua9YtIpICRCmlflD2ibnXgIuNwxcBrxrvX+1kf03ZWQXEGNc5G1ihlKpQ\nSlViD6ZtwVDjQFx4EG/dPIfrT8jgLwtnMG6Eb1WZMJmEP1w+ldgeAktTq42H3tvWpYjfqLgw/rxw\nBvedPa6bM+2EBZl55YbjmTnatf9xpXV9yzbfU1zH650CrLe46eRMrpkzmqTI4A6vcKO32tRqo7im\nGce58RaLjR/9fTXPfLHXW253i6dWIX8CvOPwOVNENgI1wMNKqW+wK2kXOLQpMGwAyUqpIgClVJGI\ntNXLdaa+ndqDXeOErMQIHr1wksfud6SqkcTIYJeHqWOTI1l861wWvriK8h62qvx88WZOzE7osqR/\nx2nZWG2KJ1d0XawIDTTzj+uPJzfD9TLIvcmTOePxj3YyaWS0y0HSXYgIj108mccuntzB/sGmQu5+\nexMA85/8iqiQABbfNpfxI6JYe7CCgspGbjo5yxsu98iAemAi8pmIbHPyusihzUOABXjDMBUB6Uqp\nGcA9wJsiEoWLStqdXejmHJevJSK3iMg6EVlXWtq3CVxN32lqtXLLP9fx9tq+zbXkJEfyl4Uz6Gld\nobHVytd7nP8M7zojh5/NPzafZjYJd5w2hvfvOJHZfdj+svtoLf/eWNB7w060WGw8scx3c812OSyG\ngL0sdY6hQJQaE0p0aKBHxTpcZUABTCk1Xyk12cnrA7BPpAMLgB8Zw0KUUs1KqXLj/XpgHzAWey/J\ncZjpqKRdbAwN24aabftDulPfdkmV2/DhRaVUrlIqNzExsX/fCI1LKKV4dOl2thXW8Mm2og7DFFc4\nKSeBZ68+jvjw7lfKugtgAD+bP5a7Ts/GJHDrKVncd/b4Pg+ZX/n+IP3NPFp7sJItBfb0BYvVRmlt\nM9sKna8IeprOvcrspIj2ldxNh6u4YFqKT4oYu20IKSLnAPcDpyqlGhzsiUCFUsoqIlnYJ+D3K6Uq\nRKRWROYAq4FrgWeM05YC1wFPGF8/cLDfKSJvY5+wrzaGmMuB3zlM3J9Fx0UEjYdRSvHAkq28Y6xy\nfZdXzqXPfc/lM9M4OTuR9PgFSQcuAAAfVElEQVQwl65z/tQUzpqUzE2vruMrJ8HqX+sLaGi1Mjcr\nnlPHJjIqruN1/+vMsdx4UpZLk/XOKKoe2ET2hc9+R3CAiRarDaXsc5AbfnXmgK45GMR1+qdwtKaJ\n4pomqhpa2VZYzc/P7Hke0Vu4cw7sWSAYWGFkQ6wyVhxPAX4jIhbACtymlKowzrkdeAUIBZYZL7AH\nrsUiciOQD1xh2D8GzgPygAbgBgAjGD4GrDXa/cbhHhov8Prq/Pbg1cbG/Co25ldx+7wx3H/OeJev\ntflwVXtlCWd8tKWIj7YUIQL/7/Qc7j4jp733ICL9Dl7VDa18Z2xgHgiO1W2TfKQaRnpcGNPSotlc\nUM3UtGhKapq591+biQ4N5KmrpvtEWo0zdCa+A8MxE98TrD9UydUvrqLF6nzy+/kfz+ScySNculZJ\nTROn/tF51nt3jE2O4KmrpjPJRQWe7lBKcfxvP6Osj6uQPZERH8aX9502aNcbKA0tFsKCAmi2WAkO\nMKOU8kpCs87E1/gEtU2t3Pzaum6DV0igiXnjXJt7tNoUn2w/2qfgBfY0hsc/HPgEuogM+h/zwfIG\nDpX3rYqGO2mrld+mwu3t3Ri9oQOYxm2U1jZz++sbqOgh9aGp1cbvP9nl0oS+YK+F3186V7HoD08v\nnMHM0bGDNqE9f0ISo2Jdm//zFuV1zdQ02efCBuN7OJjoahSaQae+2cKiv61iT3GdS72lV78/yEnZ\nCZwxIbnHdtuP1FBc09Rnf4IDTDx99QwCBmEeZ+6YeJbcfgIHyup55vO9/HtjYfuxoABTn3PEbjll\njEdVfPrKUyv28OLX+xmbHEFZXQtf3HuqTwUN3QPTDDrhwQEkR4W4PNSzKfjpG/btQCU9BKiKhhb6\nsyPnvrPHDXrp6MyEcP505TRuOikTgHHJkWx99CyevHIaj14wkWvnjraXnOmBiOAApqQObF7OnTS1\nWnlj9SEaW61sLqjmSHWj083/3sSXgqlmCPHnhdNZsqGQX3+wzaW8qWaLfTvQUyv28O5tJ5DhRJ4+\nLbZvijfZSRHcfUYO57tJiEREeOj8CSRHhVBc00RwgLmDduKU1Gjue3dLh3NOG5dIXbOF3UdrWTR7\ntEvSZd7i9tfXd1iwUIr2fbO+gg5gGrcQFhTANXNGExxg4qH3ttJqda3rVFbXwjUvr+btW+YyMjqk\nwySys9I6ZpNwZW4aZ4xPJjw4gL0ltYQEmkmNCWV2ZtygDBt7ok1cpMbJBuiITgIoJ2Un8Pw1M2lo\ntqti+7KgSElNU5c8OxEw+dikvg5gGrdyZe4oZmfG8aEhVe+skF5nDlc0csEz3/LZPad2SLAMCTRz\n/QkZHJ8RR1CAifiIILKTIogKOZbXNXeMZ1Vx2nD0oY2kqGBCAk3tAikXThtJcIC5fYXPVzlQVs+r\n3x/sMlw3i1Bc00RWYoR3HHOCzgNzQOeBuRerTfHI0m28vsq5gpAjk0ZG8eyi4zpUXPVHWq02dhXV\nsrOohgumjSS0jzXKvMFjH+7gpW8POD12xvgkXrhmpid6ti7lgekemMZjWGw2l5SDfnJiJvefO87n\neyquEGg2MSUtut+19j3NB5sK+VcPRQ0/31XCtiM1PlMiWwcwjUc4UFbPza+tI6+k++qk00fF8OsL\nJnJcuq496S1W7iqhpsni9JiIXTfAWcFDb6EDmMYjZCaE8+C54/lg0xE+31lMfcuxFIsRUSE8cO54\nLpw20qdzooYD50wewX+2FGHtNAE2MSWKJ6+axvgRviVurAOYxmOcMSGZMyYks+toDb/+YDsb8yu5\n47Rsbjklq30Li8a7nDo2iSCziUab/R/MyTkJ3HBiBrMz4wkP9r2fke95pBnyjB8RxeJb51JZ30Js\nD7W9NO5lX2kd97+7hTMmJHP7vDEA1Da3YjUW9sKCzKREhxAeFOCTwQt0ANN4ER28vEd1Qys/+ttq\njtY0saOohkWz04kODSQuLIgzxifxzd4y7j9nHNcMQPHcE+gAptEMQ77eW8pRY9tWQ4uVbYXVnJid\nQIDZxE/nZXNFbhqTB1h+yBPoAKbRDEPaSlu3kZN0LDnVnvLh+8EL9GbuIYWvaA9qfJ/O6SxvrM73\ny98fdypzPyoihQ4K3Oc5HHvQUNPeLSJnO9jPMWx5IvKAgz1TRFYbKtvviEiQYQ82PucZxzN6u8dQ\npcVi48s9JR1sSimqGgaveqhmaKCUYtuRmg62v3y+l4v++h1NfSwW6W3c3QN7ykGB+2MAEZkILAQm\nYReb/T8RMYuIGfgrdrXticDVRluA3xvXygEqgRsN+41ApVIqG3jKaNftPdz8rF7FphQnjEnoYPt6\nbxkLX1zld7+UGvfS1Gqjzkmy6tbCapZucire5bN4Ywh5EfC2Ia92ALsgxyzjlaeU2q+UagHeBi4S\nezmC04F3jfM7K3O3KXa/C5xhtO/uHkOWkEAzIYEdY/RXu0uJCglk3h9X8un2o17yTONrhAaZefUn\ns8h1IrL7/Nf7uiSx+jLuDmB3isgWEXnZQeKsr2ra8UCVUsrSyd7hWsbxaqO9VuYGqhtb2Hi4kiaL\nzakqtWb4MiszjndvP4EV/3UKt56aRUKEPaVlf2k9v/nP9j5rdnoLdypzPweMAaZjV+P+U9tpTi7V\nk5p2TyrbWpm7G5otVgoqG0mMDKaqoZXCykYqe6hNrxme5CRH8uC5E/jmF6fz0HkTCA008+oPh9jq\nI4K7vTGgNAql1HxX2onI34APjY89qWY7s5cBMSISYPSyHNu3XatARAKwr/1W9HKPzs/wIvAi2Mvp\nuPI8/oBZhKM1TcSFB3GkqonaZgtldc06eVTjlNAgMzefkkVuRiyP/mcH+RUNTE3zjYoTPeHOVUjH\nOr6XANuM90uBhcYKYiZ2Ze412EVoc4wVxyDsk/BLlb0vuxK43Di/szL3dcb7y4EvjPbd3WPYcLC8\nnkPlDYhDZ/RAme/Id2l8kxnpsXxwx4ksmDrS2664hDsTWf8gItOxD90OArcCKKW2i8hiYAdgAe5Q\nSlkBROROYDlgBl5WSm03rnU/8LaIPA5sBF4y7C8B/xSRPOw9r4W93WO4UFDRyKjYUL+Zy9Bo+oPb\nAphS6poejv0W+K0T+8fAx07s+3GyiqiUagKu6Ms9hgtiEppabYyMOfYjLtdzYJohht5KNETJjA/n\nicumAHDjSZm8tSafiSm+VctJ47uU1TVztLqJyT4s+wY6gA1Z0uPDSI8/pvh81qQRXvRG4y9UN7by\nyAfbWLr5CDYF95w5lrvOyPG2W92iA5hGo2lnyfoC3nfIxh8/ItKL3vSO3syt0Wjaqe20xajZYvOS\nJ66hA5jGJ/l6TynXvjysMl98gsmpHedJ31nbvUKRL6CHkG7kcEUDB8vrOTkn0duu+A17i2u59uU1\nlNe1EB3WVSxW415yM+I6iPHuLan1skc9o3tgbsJitfHw+9t46dsDPiVD5asUVjXy/b4yHn5/G0XV\nTbRYbTQ0W3QlDQ8THRrIBQ5JrMU1zT6dAK0DmJuobbIQGmjGJEJo4JCu5DMgbDbFnz/bw51vbmDR\n31az+kBF+7H6FivLdRUNj3NidseyTH/6dLeXPOkdPYR0E7HhQTx/zUxvu+HziMDL3x7oVkw1KyHC\nqV3jPtJiQzt8/nBLEVfklnLqWN+bCtE9sH6w6XBVF9u3e8v4yStrWbK+wAse+S8iwrRuZOpvPSXL\nqM+u8SQzR8dy/pSUDrb3Nvjm77XugfWDEVEhfL+vjBPGJLD+UAWvfn+IZduKeOvmOeRmxHnbPb9j\n+qgYvtlb1sE2f0ISD543wUseDW9EhN9dOoVxIyKJCA7gzInJjIoL6/1EL6ADWD8YER0CwFlPfUVV\nQysXTBvJk1dO18Grn9x0UhY2pdh9tJbpo2Ioqm7injPHetutYU10aKBPZ+C3IbpawTFyc3PVunXr\nXG5f1dBCRHAAAWY9EtdoBhMRWa+Uyu2tne6BDYCYMF0cUKPxJrrroNFo/BYdwDQajd+iA5hGo/Fb\n3FkT/x0HVe6DIrLJsGeISKPDsecdzpkpIlsNRe2nDY1HRCRORFYYytwr2iTaxM7TRvstInKcw7Wu\nM9rvFZHrOvun0Wj8H7cFMKXUVW2q3MAS4N8Oh/c5KHbf5mB/DrgFuwhHDnZVbYAHgM8NZe7Pjc9g\nV/Fua3uLcT4iEgc8AszGXor6EQddSo1GM0Rw+xDS6EVdCbzVS7sUIEop9YOhLPQazhW4Oytzv6bs\nrMIuv5YCnA2sUEpVKKUqgRUcC4YajWaI4Ik5sJOBYqXUXgdbpohsFJGvRORkw5aKXc+xDUc17WSl\nVBGA8TXJ4Zy+qHxrNJohxIDywETkM8BZsfWHlFJt2o1X07H3VQSkK6XKRWQm8L6ITKIPatqOLnRz\nTp+UubEPP0lPT+/ldprhhFIKpewbzg+U1ZOVqDeW+xpuVeY21LIvBdrLMiilmoFm4/16EdkHjMXe\nS0pzON1RTbtYRFKUUkXGELHEsHenwF0AzOtk/7KbZxiSytyagfPUij3sK7XXwvpoaxGPXDCRG07M\n9LJXGkfcPYScD+xSSrUPDUUkUUTMxvss7BPw+42hYa2IzDHmza7FuQJ3Z2Xua43VyDlAtXGd5cBZ\nIhJrTN6fZdg0Gpcprmnmo61FfLS1CLAHNJtN/4/zJdy9lWghXSfvTwF+IyIWwArcppRqq2J3O/AK\nEAosM14ATwCLReRGIJ9jYrYfA+cBeUADcAOAUqpCRB4D1hrtfuNwD43GJTqXU543LgmTydnshMZb\n6M3cDvR1M7dmaLL2YAUvfXOAT3ccpa3DJQIf33UyE7Q4sEfQm7k1mn6wfPtRbn99PZ1HiudNTtHB\nywfRW4k03fJdXhn3/mszDS3Oyz0PRZZvO9oleAGcOs73yilrdADT9MCuo7W8u76AR5du97YrHmPB\ntJTeG2l8Bh3ANN3SYqgyf7GrlOEyV3rauCTmZsV3sX+6vRiL1bdVqocjOoBpumX30RoAyuqaKa9v\n8bI3A2fl7hLySmo5XNHQbRsR4flrZjKx03xXfkU9pXXN7nZR00f0JL6mW+aNS+L9TUcYHR9GfLh/\nV5+tbmjlp69voLHVSkxYIP+586RuhSqiQwN58+bZLNt2lO/3lTNpZBTXzh1NWJD+c/E19E9E0y0X\nz0jFarMxIz0Wo7KR37K7uJZGQ+W7qqGVW/+5nvfvOBERMIt0ye+KCQvi6lnpXD1Lby/zZXQA0/TI\nZTNH9d7IDyiuaerweUdRDbN+9xmBZhPf/OI0QkxaPd0f0XNgmmFBTFhgF1tVQyutVhshgTp4+Ss6\ngGmGBSfnJHLx9JFd7EFaEs+v0T89zbDBmVDr3DFdUyY0/oMOYJphQ2ZCOLGdhpKxfqzt2dRqJa/T\nhvPhhg5gmmGDiHDV8R1XFQ+V13vJm4HzztrD/Or97bQO4wRbHcA0w4rJqR0TVJOjQrzkycDYfLiK\npz/fyw/7y7n+H2uoqG8hr6S2w46J7/LKWHtwaFeR0mkUmmFF50n7mqZWL3kyMEbGhJIYGUx5fQvf\n5ZUz8/EVKAVXz0pnVmYsq/ZV8O+NBZw/JYXjM+K87a7b0AFMM6xYfaCCEVEhVDe20thq7TYb35ex\n2RRf7ymltPbY1qa2jtdba/J5a01+u72q0T8DtKvoAKYZViyYksLWwmpGRAWTFBnCfWeN87ZLfaK6\noZVfL93GB5uO9N4YWH+okjdWH2LRrHS/303hjAHPgYnIFSKyXURsIpLb6diDhmr2bhE528F+jmHL\nE5EHHOyZIrLaUNN+R0SCDHuw8TnPOJ7R33tohjfjU6LYeaSG0MAAJqdGEeBHeWD7S+s47+lvXA5e\nALVNFh56bxubC6rd6Jn3GIyf3jbsykNfOxpFZCL2mviTsIvK/p+ImA1Bj79iV9WeCFxttAX4PfCU\nocBdCdxo2G8EKpVS2cBTRrv+3kMzjAkNMnPmpGTeWXeYpZuL+NvX+2ky9kj6Ohnx4eRm9F1gPiEi\nmOCArn/qO4tqBsMtrzLgAKaU2qmU2u3k0EXA20qpZqXUAezCG7OMV55Sar9SqgV4G7jIUCI6HXjX\nOL+zAnebMve7wBlG+z7dY6DPqhkahBtVJb7YVcJvP97JN3vLvOyRa5hMwojovq2aZidF8PTC6R3K\nYSul+GhLEdf/Y81gu+hx3DkHlgqscvjsqI7dWTV7NhAPVCmlLE7atyttK6UsIlJttO/rPbqghW2H\nH49eOAmTwKs/HALwmx5YfbOFT7cXu9w+OSqYN26a3SFVJL+8gZtfW0eL1cYfLp/mDjc9iks9MBH5\nTES2OXn11Kvpq2p2T2rag3mtjkalXlRK5SqlchMTdd3z4YDZJCyYdmxf5JaCKi964zqFVY3k91CM\n0ZHxIyJ56srpHYJXQaU9eO0uruWJS6dw6lj//313KYAppeYrpSY7eX3Qw2k9qWY7s5cBMYaat6O9\nw7WM49FART/uodEAUOuQ//XWmsOU+0G11bHJkdx39jjCg3qunpGTFME1c0ZztKaJDfmV7aXBV+4u\nZXexfevR81/ta7f7M+5cglkKLDRWEDOxK3CvwS42m2OsOAZhn4RfquwpxCuBy43zOytwtylzXw58\nYbTv0z3c+KwaP+O0cUlcOG0k0aEB1DVbWLHD9aGZNzl38ghie6mOG2gWnvkij3sWb2bhi6u45qXV\nLF53mM8cnnHl7lKue3mN32sdDEYaxSUiUgDMBT4SkeUASqntwGJgB/AJcIdSymrMcd0JLAd2AouN\ntgD3A/eISB72Oa6XDPtLQLxhvwd4YAD30GgQEVosNrISIwB7BVZ/YER0CCNjQntss6OolrRYe5tp\nadGsPlDBL97dwtysOG49Jau9XViQ2e9zw7QytwNamXt4cdOra6lptLDmYAV3np7NvX6S1Hq4ooGT\n/7Cy/XNIgIlpo2KwKYXFqmhstdJitRFkNrHr6LFqFX++ajoXz0jl0+1H+S6vjNPGJzFvXJI3HqFX\ntDK3RtMDNpti0+EqWq2KGekxrNxV4rMB7Lu8MuZmxbfX7a/utD1o6qgYVh/ouml7TGJ4h89takxn\nTRrBWZNGuMlbz+I/acgazSAzItq+J3JjfhUFlY3YnEly+wDvbyxk0d9X8W1eGS98tY/r/7G2/Vhw\ngDitCZYcFcy+0o6lgpwFOX9HBzDNsMRkEv581XTijAnxyJAAXvvhoFd96o5fnDOemkYLD7+3lVe+\nP0iZsWIaGWxm2qgYKuq7btgurmlmdKeN6nF+Lo3nDB3ANMOW7KRI/vP/TiI6NJCU6BD+sHw3u476\n3vaaxMhgfn/ZVA6WN3C0ponZmXGcMjaBEdGhlNe1MCIqBLOp62R85+1DGfH+V3mjN/QcmGZYkxoT\nyqs3HM8Nr6xlSmo0SZG+WeAwITIIs0mw2lSHoeC0tGg+//k8mlqtPP/VPrYUVHPPmWNJigzmwme/\n7XCN577ax5wx8ZwwJsHT7rsNHcA0w57MhAgqG1qZnh7js8OslOhQ1j88n9UHKiirayYlOoS6ZivT\n02IACAk087P5Yzucc9PJWTz+0c72z61WNeRUmHQahQM6jWJ4opSirK6FxMhgb7syqNhsivG/+oQW\no2Z+kNnE7sfP8YvcL1fTKIZWONZo+oGIDLngBfaFihtPzmz/3GK1caDMvjJ5tLoJq4+uuvYFHcA0\nmiHM3WfkkJVwLB9sV1EtVz7/A3Of+Jz73t3ss6kjrqIDmEYzhAkJNPPrC47V8lx7qIKthdUoBf/e\nUMjL3x3woncDRwcwjWYI0NRqpbqx1enm7HnjkjhzYjJgz+o/OefYKuSba/Kpb7Z0Ocdf0AFMoxkC\n3PnmRqb996eM/9UnPLBkS5fjv7tkCgkRwewpruO40cfKUu8vreeK538gr6TOk+4OGjqAaTRDgIQI\ne/pHq9XGdSdkdDmeGBnMg+eOx2wSPt9ZzGnjjhUz3FFU45MJvK6gA5hG4we8v7GQBc98wx+X73J6\nfGO+varsrxZM7FD/3pHLZqbxyg3Hs/ZgJaFBZmY5CIT4azaVDmAajQ+zbGsRDyzZwv1LtrCrqJYL\nHEphO3La+CRGxYVyw4nH0iaczYednJPI/eeMZ7lRW//S4+wSEq1W/6zOqhNZHdCJrBpf41B5PWV1\nzYQGBpCREEZYUPebZ1qtNqw2RU1jK39dmUdhVRNX5KZxtpPSOUs3H+F/Pt7JJz87mXv/tYXK+hZ+\ne8kUxo2IdOfjuIxOZNVohgCj48OZOTqOiSOjegxeYK8TduofVzLrd59jU4qD5fWcZaw+dubCaSNZ\nee88okODeOyiyazPr+TZlXnueAS3MqAA1p0qt4icKSLrRWSr8fV0h2NfGorZm4xXkmEfNPXt7hS+\nNZqhzLbCaopr7KV28isa+cPlU3vcNhQSaBcHGREdwjmTRvCrBRM84udgMtAemFNVbuwKQxcopaZg\nF+P4Z6fjP1JKTTdeJYZtMNW3u1P41miGLHOy4jl1bCKpMaHcfHIWx6W7ruL98IKJPluJoycGVI1C\nKbUT6BLllVIbHT5uB0JEJFgp1ZN21UXAo8b7d4FnO6tvAwcMYY9ZRrs8pdR+w4c2he+d2BW+Fxlt\nXjWu+1x/nlGj8RdCAs28+pNZvTd0QmovQiG+iifmwC4DNnYKXv8who+/kmPRr4P6NuCovt1ZZTu1\nB3tPCt9dEJFbRGSdiKwrLS3t7zNqNBov0GsA66cqd9u5k7AP5251MP/IGFqebLyuaWvu5BL9Ud92\nWZUbtDK3RuPP9DqEVErN78+FRSQNeA+4Vim1z+F6hcbXWhF5E/tw8DWOqWkXuKi+TTf2doVvoxem\nVbk1mm6w2hR1TRaiwwK97Uq/cEtFVhGJAT4CHlRKfedgDwBilFJlIhIILAA+Mw63qW//gIP6togs\nBd4UkSeBkRxT3xYM9W2gEPtE/yLjnDaF77fpqPCt0WiADfmV/OnT3WwpqCbIbOLqWelcPCOVILOJ\ndD+qnT/QNAqnqtzYVbGzgV91SpcIBpaLyBZgE/bA8zfjnMFU3+5O4Vuj0QAxoYGs3l9BbZOF8voW\nnl2Zx/wnv/K7PZE6E98BnYmvGU78fPFmlmwoaP88IiqEr34xj+AAsxe9sqOVuTUaTY88eN54NhdU\nkRwVzOj4cOaNTfSJ4NUXdADTaIYpCRHBfHbPqd52Y0DovZAajcZv0QFMo9H4LTqAaTQav0UHMI1G\n47foAKbRaPwWHcA0Go3fogOYRqPxW3QA02g0fosOYBqNxm/ReyEdEJFS4JCbb5OAveTPUEE/j+/i\nz88yWinVa4E+HcA8jIisc2WTqr+gn8d3GUrP0h16CKnRaPwWHcA0Go3fogOY53nR2w4MMvp5fJeh\n9CxO0XNgGo3Gb9E9MI1G47foANYDIvKyiJSIyDYH26MiUuhQ6/88h2MPikieiOwWkbMd7OcYtjwR\necDBnikiq0Vkr4i8IyJBhj3Y+JxnHM/o7R4uPs8oEVkpIjtFZLuI3G3Y40RkheHHChGJNewiIk8b\n99siIsc5XOs6o/1eEbnOwT5TRLYa5zzdpvvZn3v081n88ucjIiEiskZENhvP89+D7cNgPqfPoJTS\nr25ewCnAccA2B9ujwL1O2k4ENmMXLskE9gFm47UPyAKCjDYTjXMWAwuN988Dtxvvfwo8b7xfCLzT\n0z368DwpwHHG+0hgj3HNPwAPGPYHgN8b788DlmFXgJoDrDbsccB+42us8T7WOLYGu8iLGOeea9j7\ndI8BPItf/nyM548w3gcCq43vx6D4MJjP6Usvrzvg6y8gA9cC2IPYZeTaPi83/pDnAss7tzN+YcuA\nAMPe3q7tXON9gNFOurvHAJ7tA+BMYDeQYthSgN3G+xeAqx3a7zaOXw284GB/wbClALsc7O3t+nqP\nATyL3/98gDBgAzB7sHwYzOf09t+k40sPIfvHncZw5+W2oRCQChx2aFNg2LqzxwNVyi4P52jvcC3j\neLXRvrtr9RljODAD+3/6ZKVUkXG/IiCpn8+Uarx35l9f79HfZwE//fmIiFlENgElwArsPabB8mEw\nn9Nn0AGs7zwHjAGmA0XAnwy7OGmr+mHvz7X6hIhEAEuAnymlehICHMxn6us9XMLJs/jtz0fZ9U6n\nY1eTnwVMGEQfBvM5fQYdwPqIUqrY+EWzYRflnWUcKgBGOTRNA470YC8DYsSuVu5o73At43g0UNHD\ntVxG7IroS4A3lFL/NszFIpJiHE/B3gPozzMVGO+d+dfXe/TrWfz952M8QxXwJfY5sMHyYTCf02fQ\nAayPtP0RGlwCtK1QLgUWGis3mUAO9gnttUCOsdIThH0ydKmyTyysBC43zr8O+zxO27XaVvYuB74w\n2nd3D1d9F+wq5TuVUk86HHK8X2c/rjVWCucA1cbwbzlwlojEGkO0s7DPmxQBtSIyx7jXtd08kyv3\n6Nez+OvPR0QSRSTGeB8KzMeuOD9YPgzmc/oO3p6E8+UX8Bb2YUgr9v9GNwL/BLYCW7D/gFMc2j+E\nfd5iN8bqm2E/D/sq2T7gIQd7FvZfrjzgX0CwYQ8xPucZx7N6u4eLz3MS9iHAFmCT8ToP+7zG58Be\n42uc0V6Avxr32wrkOlzrJ4Z/ecANDvZc7EFjH/Asx5Kl+3yPfj6LX/58gKnARsPvbcCvB9uHwXxO\nX3npTHyNRuO36CGkRqPxW3QA02g0fosOYBqNxm/RAUyj0fgtOoBpNBq/RQcwjUbjt+gAptFo/BYd\nwDQajd/y/wEKIt8qW8kSggAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "protected_areas.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Conversion to a common Coordinate Reference System\n",
    "\n",
    "We will see that both datasets use a different Coordinate Reference System (CRS). For many operations, however, it is important that we use a consistent CRS, and therefore we will convert both to a commong CRS.\n",
    "\n",
    "But first, we explore problems we can encounter related to CRSs.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Goma](https://en.wikipedia.org/wiki/Goma) is the capital city of North Kivu province of Congo, close to the border with Rwanda. It's coordinates are 1.66°S 29.22°E.\n",
    "\n",
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Create a single Point object representing the location of Goma. Call this `goma` (watch out for the order to pass the latitude and longitude!)</li>\n",
    "  <li>Calculate the distances of all mines to Goma, and show the 5 smallest distances (mines closest to Goma).</li>\n",
    " </ul> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "from shapely.geometry import Point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "goma = Point(29.22, -1.66)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "dist_goma = data.distance(goma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "301     0.226353\n",
       "1868    0.235082\n",
       "1865    0.252101\n",
       "1067    0.263424\n",
       "1538    0.264856\n",
       "dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist_goma.nsmallest(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The distances we see here in degrees, which is not helpful for interpreting those distances. That is a reason we will convert the data to another coordinate reference system (CRS) for the remainder of this tutorial."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Make a visualization of the national parks and the mining sites on a single plot.</li>\n",
    " </ul> \n",
    " \n",
    "<p>Check the first section of the [04-more-on-visualization.ipynb](04-more-on-visualization.ipynb) notebook for tips and tricks to plot with GeoPandas.</p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd729500c18>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OKL57ananyxetLWJ5ftu5ogbFhvPSd2cyrN2QTGEOG/ddNpFvTO3y/2IA6hqd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\nKaWUCgqasJRSSgUFTVhKKaWCwv8HXxznMEMgDqwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = protected_areas.plot()\n",
    "data.plot(ax=ax, color='C1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You will notice that the protected areas and mining sites do not map to the same area on the plot. This is because the Coordinate Reference Systems (CRS) differ for both datasets. Another reason we will need to convert the CRS!\n",
    "\n",
    "Let's check the Coordinate Reference System (CRS) for both datasets.\n",
    "\n",
    "The mining sites data uses the [WGS 84 lat/lon (EPSG 4326)](http://spatialreference.org/ref/epsg/4326/) CRS:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'init': 'epsg:4326'}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.crs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The protected areas dataset, on the other hand, uses a [WGS 84 / World Mercator (EPSG 3395)](http://spatialreference.org/ref/epsg/wgs-84-world-mercator/) projection (with meters as unit):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'datum': 'WGS84',\n",
       " 'lat_ts': 5,\n",
       " 'lon_0': 0,\n",
       " 'no_defs': True,\n",
       " 'proj': 'merc',\n",
       " 'units': 'm',\n",
       " 'x_0': 0,\n",
       " 'y_0': 0}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "protected_areas.crs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will convert both datasets to a local UTM zone, so we can plot them together and that distance-based calculations give sensible results.\n",
    "\n",
    "To find the appropriate UTM zone, you can check http://www.dmap.co.uk/utmworld.htm or https://www.latlong.net/lat-long-utm.html, and in this case we will use UTM zone 35, which gives use EPSG 32735: https://epsg.io/32735\n",
    "\n",
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Convert both datasets (`data` and `protected_areas`) to EPSG 32735. Name the results `data_utm` and `protected_areas_utm`.</li>\n",
    "  <li>Try again to visualize both datasets on a single map.</li>\n",
    " </ul> \n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "data_utm = data.to_crs(epsg=32735)\n",
    "protected_areas_utm = protected_areas.to_crs(epsg=32735)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd7292c4898>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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do5Wz/u9rJz8xO2eP7ctvzx7JkN4JAeiZwe4j1TyzbBfLtx9xOvaSFBvJ01cd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\nmUajCXm0kGk0mpDn/wOjA5LVQCuFhgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = protected_areas_utm.plot()\n",
    "data_utm.plot(ax=ax, color='C1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### More advanced visualizations\n",
    "\n",
    "<p>For the following exercises, check the first section of the [04-more-on-visualization.ipynb](04-more-on-visualization.ipynb) notebook for tips and tricks to plot with GeoPandas.</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Make a visualization of the national parks and the mining sites on a single plot.</li>\n",
    "  <li>Pay attention to the following details:\n",
    "     <ul>\n",
    "      <li>Make the figure a bit bigger.</li>\n",
    "      <li>The protected areas should be plotted in green</li>\n",
    "      <li>For plotting the mining sites, adjust the markersize and use an `alpha=0.5`.</li>\n",
    "      <li>Remove the figure border and x and y labels (coordinates)</li>\n",
    "     </ul> \n",
    "   </li>\n",
    " </ul> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tbe3pad30PqjlZMk6sebKI4BXsSIH6D2l3IwVPeyOVbOuh7UjccCR2BTtwhLv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ebNmendOYdf6Wj9uqf7czjeAL4L/k1gocf/0rPqoG7uz/Y2P//JQS73MLb2rlSlVC8fAlwzhHvI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\nSUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = protected_areas_utm.plot(figsize=(10, 10), color='green')\n",
    "data_utm.plot(ax=ax, markersize=5, alpha=0.5)\n",
    "ax.set_axis_off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tbe3pad30PqjlZMk6sebKI4BXsSIH6D2l3IwVPeyOVbOuh7UjccCR2BTtwhLv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ebNmendOYdf6Wj9uqf7czjeAL4L/k1gocf/0rPqoG7uz/Y2P//JQS73MLb2rlSlVC8fAlwzhHvI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\nSUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# alternative with constructing the matplotlib figure first\n",
    "fig, ax = plt.subplots(figsize=(10, 10), subplot_kw=dict(aspect='equal'))\n",
    "protected_areas_utm.plot(ax=ax, color='green')\n",
    "data_utm.plot(ax=ax, markersize=5, alpha=0.5)\n",
    "ax.set_axis_off()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " \n",
    " In addition to the previous figure:\n",
    " <ul>\n",
    "  <li>Give the mining sites a distinct color based on the `'interference'` column, indicating whether an armed group is present at the mining site or not.</li>\n",
    " </ul> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KVjIDeDKAD/0f+3g4A46L3OlYOZjO9ig2AfOxZfYYGAmsJPc9cB7bMzmuzeOntv03Tf69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\nnTwsPbzclU0eXnE38LcgVT8fmD8pxb8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GG8nzff1BZo/rzxqakdUz9kbOgMqx61YnuxVl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\nGjo5JjJnMHQxvJyYh5HoQmv4MQHmxI1y1BDkizWnHbY7BliqHHU28Fp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s3PxWOXSh6yen\nVlbw1vxvBh+4MZKsDjxyS8H/vbrkvg9fzO4+/5uMkT1zqu888/ZPXeo4YMpRQUTs9xSk3djP6JuW\nxK6DFDk6hS0rMtm8PAb+rc7cdOWop7WtF9WdZ+g4jDNnMHQhtK0rESkBlKMGIp8B/0UqUNsaPxIV\nq2xqYA3a1q5yVC5QmmBBYkPiOAvJh9sPifLsh1ws1FwkvLaDO9wusAXROywEqps5/yOkUKR7kk+7\nJ18cSc7brfxERBrk360xLLNn9LpvXsw6eO7MbkopeOHfKb32ObR4r8NOLNhw2IkF66inWMGrML+T\nRvJozxrTnV1iWegNGXzwRDbqhwEMvOJ9VpdFQT4zbgParI2fofmYalaDoYuibb1a23o5cDjSJLu5\nye8toRfSVzJutK2LjCPXefG05xZoWz+ibX2utvV4JOozxbs917EWtg7vOPQW4EHgH82V4Qi7oQgw\nCrgyu0/1ygOOLFR7HFjcHZjuRvLOdiN5LS5Oyu5d1cvn13j14jpWDa8/3vM5YA4wH/ignmk9qMeR\ns6qSGPTVCIbNGEtVSRJJKTHKSiwKfkqlZ7rFNXtm1w7hH+C1DzR0EkwHCIPBAIBy1J+Bu9twi0ok\nr2feDh6pMRgACFjBJOR3emPYDS1panxR/piBGZnuJ0rRA3GqNJIXureVm1/Y0DyvgGIcIqg8O+yG\nqgC+fWW33OpK1nz3RTfmftGNpQvSKqvK/ZuAMWE3VG8xi3LUAETyJ6X241krezHwm+G4PpfoiM30\nD0QYvngA/Zb25xcnrUcPK+JXb62pnXAaBcZ62paGDsZE5gwGQw0b23DtV4CDta2/N46cYSfieuBV\n4IOAFdynqcHdursblOIjth1Bu4iESIPyLgEruB8S3XwCuAyJogMw8djvItefNeLSRd+mR35ckF5d\nVe4v9dbarouGclSyctTDSIu6lLrPV3WroFuPGMdNqWKvPSr4LFLOV4NWsvvl+eTuUsq6siiDu/0s\nM8uH5NwZOgEmZ85gMOBJdhzX5MCWca22dbOOVg2GzoQXgRsMbKgT8ToWcZx6Af8JWMFjEA3DgrAb\ninpzLaSCvCjs5le6kbx3kZ62kxGnbh5S0FPfvtlIy7Q9vD0ygPdqj3mz9KU7AlbwLiR94XjgubAb\nWlvPchcBZzf0Gst7lrLnOSsYk5vC6FSXRd+nMGdjJffO28K0CVmUxzRnjO6OM3tz7WnRhtYztC/G\nmTMYujheQvSDwG8TvPRK4DJt6xcSvK7B0N6cBRwAbAhYQTvshkq9x78ExiKnXGOBt5B8tbkBK3gb\nEnm7ABGr3itgBfPOnN6n+LcXbPjYspgDPA08ZOXmNxStrkLEr1O9tVSf/lXL3EjeXsBqKzc/Alvz\n+q72bg2R29SL3GxVotJ8xFwojUqh7YLCKtZXxEj3WUTKq+pO+R1wY1PrGtoe48wZDF0U5ahUJBo3\nHZiQwKXLgZuB27St21wk1WBoByYgsjq9vVuNM3cNEg3L8u5nI5p6o5GcuCrEkStBnD21YFZ6jy2b\nkg7I7hNbBmDl5jdYUBF2Q6UBK3glUODN/2nKbzaedsFhIw4eNq5i9QnnTzhy+EHfF8T5Gno1NeDF\nZSUsL4lSVOWyqFCKdteXx/j77AL6piUxr2CrM+ci1bjzlaOUSZ3oeIwzZzB0XZ5BjokSyXPAldrW\n8erIGQw7Av9FetfOQNrAARB2Q+sDVvBI4A5EsuQDYCjwObAZKXD4DInOAbBmWSqrf0xZV14ardQu\nqYOaiJeF3dCagBW8DJgIFD57T9/v0cq/ZF76gPzvUo96eAFPxvkamqzCrXbhy3XbD1tdGmV1aRTg\ndqTq/VMgZjqpdB5MNavB0EVRjrIQsdf/JGC574Bp2tafJGAtg2GHJWAFk8JuKFbrvkJ6FN8L+Ebt\nWlw1cXLplpirUuZ/nbFoyyb/AU8ufy0u7TpZS8cABVqDeirsvvD7eOYqR+0BPArsGu9rUcCUAWmM\nzPL/+NbKstdWlkQvNVG4zolx5gyGLo5y1GHA0UhHiMnNnL4JOWp62GjBGQz14xVQ3K+S3LF3v5k/\n/N/X9++zelkKxQVJ2o1Zj7kx6/ywG2ryy9hbpxJIQqJ+54bd0CPNsUU5qgQppGiItcjf9fgJPZO5\nbs+exQf1S/uqV5rvbSs3//bm7GVoP4w0icHQxdG2fk/b+kLgQKTK7jLkiKgxYsBdwCht638bR85g\naBgvUnfx7pNLrh06pnLzuH3Lyoo3+XzRKsvvxtQ5xFlEEHZDsfTM6FUDR5aW/+W+H/VDH83/90s3\n7fOLeO3wovGbmhj2KPJZ8E+fpb44emi3eb3SfMOBw91IXo949zK0LyZnzmAwAFub0C8DbleOWopo\nw9XH+8DF2tbz2804g2EHwzte9YXdUDVA2A2VuZG8z4DXfn3Gpj2euydnCqgkT3IuL951H/l0YZI/\n2U3N6A6ASvIXf4C0youHIxCJlcY4DfintvUVbiRPAY8Aa5DCpj5ISzNDJ8NE5gwGw3ZoW7+KKNuf\nByzwHt6CVL8eZhw5g6F+AlYwL2AFA8B1wIMBK3hwzXNWbn4UuKFX3+j5lmIaqGKkoGJavOv3zHFT\nfeK6KUAlp2mlHHW6ctTdylFDmpi+HGjqOHcQ8D/lqCM8yZS7EJmhT5CLvXoJWMFxASsYDFjB/nG+\nFEMCMZE5g8FQL9rWs4BZylFPIlILw4DXTQK0wVA/ASs4ALgHGIOkIrwEHAl8XDPGkyJZ8U4VDwAP\ntGCbQjRVFWUkx2Lw508iGnjMe64njXdlmIgIFA9s4PnnERHkl/AieFZu/rfAt24kL9V7jeov96zI\n2/vQ4pzMHjEFzDm8/24pwCVILt9ewF9a8LoMrcA4cwaDoVG0rSuQatXvOtoWg6GTk4ZIk2xBjiQH\nAU8leI/uad14ak1J9bijwz/t+W1hde0j1pOVo+7Utv66gblrEYevPs4Anta23q6rgydS/Eeg4rAT\nN65ePDflwqoqlX3Q0YUr0jL0f4CHvaEK0aAztDPGmTMYDAaDoZUErOChwFRgNhLVCiPi2RsSvNXj\nn0fKL7v9u4Ldv9tUXV+u3G3AQQ3M/Rj4F7AfcGitxz8F/lufI+dxKLAL0GfkrmUZvzhqS2/XVUnR\najUM9N5hN3RrwAr+E4ngf9mSF2VoHUaaxGAwGAyGVhCwghmIjlwF0nrrOmBtTfFDI/NOQjpIvA08\n7rXlapSNc3fpddBHS19cUFjVkMMGMKQh4W5Pb+594EOkRVlfYKq29Qf1jXcjef2BhxDZoiWFm6zh\nqWk6K1atVWoGlUk+3gGCXj6goYMwkTmDwWAwGFpHBZADjEIqP9fF4cj1B65HmtX3Q/q6rmtg7ECg\nx7Cxpb+Ixobdsbc7zDdxtzX8d/y3DS1/JHB/A88dg8gPfQucieTYrW/E1OeQSJ4FjOzRy13rumhS\nSbUsZgJLMUerHY5x5gwGg8FgaB0a2IhUpqYjvVobc5BAerdu8f6NIv1Xa4SBhwIrw26oOmAFBwE2\n0O2nZanHaI0fDVnlA0npl09lr7L61laN7PuAtvVaAOWoBUi+27xGxuexTfkiCcCyWItIlNwOzLZy\n840z18EYZ85gMBgMhlYQdkNuwAo+hxyZfoQ4dk2xCOnpOgF4LOyGqjxtuqcQWaAFASt4PNALSAbc\nqgoVTfJprZRSRVss3OQGTzYbKoCgxpHz/l8JzG1orBvJy+TnGnbrkP60Y5DcwPfM8WrnwOTMGQwG\ng8GQAAJWUMXTlquR+QMRJ08BJYhTtwY4CRgAbC7PKP1nLCmWmX/4XDbvEqlvmSogU9u6qqV2ALiR\nPD/wBbCnZ48bi7FpzbJkf3mpVTFiXMXz/oH5F7VmD0PiMJE5g8FgMBgSQGscOY9xQDWQgjhQK701\nn6wZoBw1zRvXEMu9NVrLQUgFa81rcosLVJZS2r/sh9QeWzYn/WHf32GcuU6C6QBhMBgMBkPnYA4w\nHxH2faCuc6gc5aPp1l95wJ3KUY3lzcXDHkiUTwNlwP+Wzk/Xz9/fmzkzMvn8raxkN5IXdxsyQ9ti\nnDmDwWAwGDoBYTe0AdGqm4LIm9RlGPH1Yb0QeEg5KqsV5vwCkVmpAv5q5ebvs/6n5Bvmf92Nn5Yl\n61MuXh8FNrVifUMCMTlzBoPBYDDsAChHnQg824wpG4BrgUcaEQSuFzeSNxdxHpOAl63c/FPcSJ4C\nrgGOAK6xcvNnNGdNQ9thcuYMBoPBYNgxOKCZ4/sg/V9zgBuaOfcZYDrSYzbHjeT5rdz8auDv3s3Q\niTDHrIYORTnqDOWoeI4NDAaDoavTXGeuhguUo1JqP+BG8iw3kne8G8mz3UjeLvXMuQ2RIXkV0czr\n0cK9De2AceYMHYaXoBskTvVw5SilHGV+Zw0GQ5fD+7zs2cLpfRF5k9oM+vSN7uc8elPfAyOr/H+u\nO8HTj3sYyZn7iCby49xIXpIbyTvYjeQF3EheSmNjDYnHfDEaOpKTgWXa1rE4x48BPlaOmtCGNhkM\nBkOnQ9taA39txRKX1q5wvfCXIwfcc82A/d5+utc+9unD9q1vgpWb/ypwjpWb/3AcXR72A84FzgAC\nrbDT0AKMM2foSL4HrmjG+JOAA4GHlaOS2sYkg8Fg6LQ8DUyjgR6uTbAr8KuaO/nfZaRt2eQrKCux\nNq5YlFrc0KRmtOpSbGsjZj6f2xlTzWrYIVCOGgm8h1RXgTSovrG5FVoGg8Gwo6MclYHIj1yMHKHG\ny0xgsra19nrAXocIA98WdkMNtgCLBzeS5wMORgSPP7By8ytas56heRhnzrBDoBx1HvBvIB9YC+yG\n5HDcBDxunDqDwdDV8ESED0eONn+N9HBtiiu1rW9rC3u83rITkFO/uWE3FG9Uz9BKzDGrYUehyPt3\nPdJmZgUwAknQnaMcNamjDDMYDIaOQNs6qm39prZ1EOgHXAB808S0W5Wjft9GJk1CUmcuQ0SHDe2E\nceYMOwoYB1LGAAAgAElEQVSV3r81uRiFtZ6bANzWSrVzg8Fg6LQErGBKwAqeH7CCNwas4Mi6z2tb\nb9a2vk/beh9gb+CNRpb7j3LU1DYwswfbcueMlEk7Ypw5w47CiUjfwv28+3U/KHqzLXpnMBgMOw0B\nK2ghuW37I/IkwcbGa1vP0rY+moaduiTgj4m2E9Glexd437sZ2gmTM2fo9ChHpQKrkJ6ENdG3L5AP\ntho+17ZuqaCmwWAwdEoCVrA/cBVywRpDdDlfC7uhF+NdQznqMOBFoFuthzcDfbStf5bXtm7OuP4P\n/S339Fkfd+9fWuR7srWFEYb2wUTmDDsCI5Gih9rHqHVb0e2rHDW0vQwyGAyGduJgJBJ3JHIicQPw\ncnMW0LZ+DzgE2Fjr4Z6IXMlW3Ehe8vIfUm+b93XGleVl1nmgPw5YwfsDVrCbV9xg6KQYZ86wI3A4\nUFDrfgzYvc4YH3B7u1lkMBgM7YMC0pG84eFhN7SkJVWi2tazgMlIusoCYBYwvM4wX0b3mK+8LMnv\nRvEBaeD+ITklumXsXsUvtO5lGNoSc8xq6PQoR40C7mWbqviPbP8hBPATMEzburq9bDMYDIa2JGAF\nM4GXgKHAY2E3dGNb7udG8ib86/IBl73z356nwjZx9tS0mN7zkJI+178R3q6tV8AK+oFTgSHAE2E3\n9GNb2mjYHhOZM+wIbAQG1LrfrYFxq9rBFoPBYGg3wm6oGPglUszwj7bez8rN//6ypz46A6wZoLV3\nQ1lw9l/XHNbAtLHIMe4gtu8Ba2gH6uYdGQydkZOQSq4aioCcesb9hDh9y9vBJoPBYGhTAlZwNHAY\n8GnYDX3bztsfDnyV3j06MS3dZepvN6sBQ6sfdiN571q5+ZvrjN0EjEI+l03nhw7AROYMOwJ1mzY3\ndIz6GyTMbzAYDDs03tHlk0jLrscDVrBHnecPDFjBEwNWMK0t9g+7oShYV/XOjZadfsV6ho2uomC9\nlQa8Wc/wKkTI/T2gm9cqzNCOGGfOsCOwoc79XKCsgbFNqZ8bDAbDjkASklJSgfQ7Ta15ImAFD0S6\n39wGvBSwgm11EfvhqsWpq568PYdn7+qj53yWCZBRz7jNwOdAGvBO2A3F2sgeQwMYZ86wI1BXPy6V\n+p25HwDTo9VgMOzwhN1QBXA58C1gh91QpNbTA5A+rN2RfLXLA1bQF7CCFwas4PUBK9g7QTbEMntE\n39jwUzLLF6Ux64MM7bqMdSN5891I3rDa44B7ECHiZxOxt6F5mJw5Q6dGOSobWIP8ruZ5D69DKrvq\nMgY4G7i/XYwzGAyGNiTsht4C3qrnqVeR3qdHAPMQuaazgUsQKZMc4E+JsKGowL8CNIA69DdFbNlk\n+TK6u2N9fm61anWiCLshDZQnYk9D8zGROUNnpxsSmUtlW2HDAEQFvT76tYNNBoPB0GGE3VB52A39\nCZgKPARkAtcCfRDPK4GaY+otIAaKVYtTVGmRj7kzM/j7eYOOf87e/5zE7WNoDcaZM3RqtK1XISKX\ng5Fjhe+RKF1hA1MayqUzGAyGnQpPz20GIga8ComMvQHYCdxj2YARFcdl96mufvSWXO6a3p8H7P6q\ncKPPWv1j8v8lah9D6zDOnKFToxylgBHe3f7ABOAzxLGrD6M1ZzAYuhLFwNdIYVgRcszas+bJgBXM\nDFjBfQJWML32JOWofspR5ytHPaYcNV856oyGNnhs8ZtvHHzslt/mDKhesujbdLdH75hWStGzT3XG\na7fsV19BhKGdMR0gDJ0a5ahdgX8ihQ1VSG5Ida1bBnA82/I/p2pbf9ABphoMBkOHELCC/ZEI3SDE\nuXs07IaufPTSAydHViU/9MPsjPQ1y1MWAEe/b7+QA/wF+AO1KmQ97gIub6yLzj3nHdR/8IjKFZbf\nxe+j8tVH++x63//eNB0fOhjjzBl2eJSj9kP6sq4ETta2NmXxBoOhyxCwgr8C/ovkzmngydxBlTed\ne92a1yvLrWExV5XefdXATZ+c9uH/lfQvvJ3tnbjafAgcqW3doPjvtL1/efeA4ZVHr1qS+uGi/2Wc\na6RIOh5TzWrY4dG2ngns19F2GAwGQwfxAxBBnLQS4M2KcivbSkIn+XVJrEKl+JLdV0r6FV5E447c\nUuCvjTlyAAtnd5u2cHa3vwDl4f9v787j5KjqvY9/Tk32hCwkgZEliUBGQghEIYCoLEIjoKACjSI7\nKKiAL0W5qPfhKYqLyNUHryigrCJyRWlQRAWxQdlBCJAQCDghhAAhk4UlezKZqfP8cWpIpzMzvUxV\n99TM9/169YvuqlNVv2EI/ctZfifM2X9eN2Nsy+uDRp5w6WML4vqBpDLqmRMREUm5jJfdHjgZN2/4\nNmDGbnuvOWm/w1aMHTmm/ZrPrP6XAR4ucZvrrG/PruS5D980Y/ehw9pvtTDsxaeGX3n6Tx65urqf\nQHpCPXMiIiIplw9zi4DLATJedgZw3tyZw725M4ffmg9zjxKYHwCMWDKSCY83sWHEel7/WDMbh7UW\n3mZVpc9ta2UfM8Ju1dbqbQTOzHjZh/Nhbk4MP5JUQKtZRUREUiTjZbfJeNkDMl62sYsmQ3GrWkM2\nbb/1b9Nu2PmB3Rn9+li2eXk7xryybfF1Wxd+iFbBXpTxsgd0FYu1Jr96xYDlrzw/tPH+O8ZY4IKM\nlx1V3U8m1VLPnIiISEpkvOwA3GrU8cC7GS97QT7MtRY1exIYi9vT9d7o2HMA7QPbXJoHbNhqi7Kc\nJ5jAXGh9uyzjZQcBZwFrgNMzXnZWPsytLL7g8nMm7gn2NWBnMGOBybiqA1JDSuZERETSw8PtjLMG\nGIb7Ht8smYuSuz8WXfeSbbDr5x02Z8i4eY2sHreSFRPfLr73ENw2YAGuHFQLsAOwHHh/UUTY0rQd\ncAbw7uAh07bZsN5bixuibWlosLO/e81CFW+vMS2AEJGaMYGZCpyO+9Jotr79WZ1DEkmdjJfdDTgQ\neCwf5p4vOucBe+N65Z7Mh7n3a8aZwDwFzChx+7nWt1Oje20F7AIsyIe593fdCVuazgb2AQbf9rPx\nf7v58u32BcyEprVTv3jusgnb7LBxzrT91pzqNTav6PlPK+VQz5yI1NKHgG9H78+sZyAiaZUPc3OB\nucXHM152LHA+cCSwALgJt71Xh5mUTuYmmcAY61ubD3OriIZniywA9gc2nPCNZU+eeNljt2a87I5H\nnfb23evWsNVbrw08eNePsPdgUAH3GlEyJyKJMYE5DzcUdAvwVeD7BafH1SUokT4o42WnAxcDH8Yt\nfJiAWwhR6FbgayVuNQz3Z3NZN23yuIRurdfYvCjjZbduGGA/MW/20A+sXtEwDiAMufL5Jw7xl7w+\n6HyvgeeWtww8/5ZX7y6e2ycxUTInIkk6A5gO/ABoKDqnPR1F4jMDN4+uFTd/7Z/APYUNDvjvo55u\n2fWNpUNWD93mzRmv8k7Tkq7uNZFukjmvsdkC8woOnTJwUHjQ7MdHjNx6242M/0AbK5Y3TBk6LPz5\nqK3blq1b23D45GnrfofbV1sSoNIkIpIIExiPTavaihM5gNE1DEekr3sQWIEb2vwG8N18mFsDbo5d\nxsv+eND6wS/vMGun8eNf2Y7d79yHhtbO/lgCbgi1Eq3r13oTV68YsGHtygF2XGMrO01d37b7fmuG\nt7WZMUNHtK9unND6WpU/l5RBPXMiEjsTmAbc/Jzp3TQrHgISkSrlw9y8jJc9D7D5MBcWnT4Bt+ho\nksEYgAGtAxm8Yihrx6/u7HbfM4G5wfq23FWpfwBz1pqVDasGDwsXTp6+bscN6xoa9jpg1XMjR7ff\n1N7OYx896Zk3q/7hpCStZhWRHjOBGQkcgStfMAo3L2e/EpctBPa2vl2ecHgi/VrGy34ROBw4Fhge\nEmIJTduwjawdu4rnTnyUcHBx/sf3rG8vL/P+uwEX4ebbtQ0cFLZtve3GsQ0N3P/rV+8u6x7SM+qZ\nqwMTmBnAR3BLu0cDx1lfWbWk2qlApWVGJuImbJ8bezQiUuh24ClcwnXNuhFr9xvYOnAc7YYRi0cz\n7qXtWTr9jeJrLjSBudb69t0y7v8a0IxbdPHSxlbvzCVvDG6jqP6dJEfJXH38CDgoev9HXD1uJXOS\nKiYwtwAv4KrNl1oh15Ut9hMSkXhFw66vRh+PMoG5bK/rD/zeVkvGYICtlo5iqX3j/Z0hIqOBS4Dz\nyrj/2oyXDYBBwGm4simj6KR8iiRDCyDqo3Didw6YWq9ARHrgKOC/gYeAKVXeo7vyByKSjMWzv/g4\nq7Z7l7f2XMjgNUNoaO20b+dcE5gu92UtlA9zYT7Mrcf1AL6DS+TmxBeydEc9czVmAvMbYFrBoeNw\nS8rPr09EIlVbRs9XpC6KIxARqcg9bSM2XvbmjPkjxs5v5J0PLqV9UFtXbW8ygdmju8UQGS/bgPsu\nmwzchvs+25gPc9rWq0bUM1dDJjBDcXPlCteDT8XNYxBJm7/28PoW4OYY4hCRCljfzsdwzpJpbzL3\nszNpmf568RBroZ2Bk0vcchfcrhPbA6fkw9wKJXK1pWSuhqxv1+Hmyu0NfBl4HjjB+nZNPeMSqdLT\nPbx+hvWteuZEaijjZT+c8bJXHRIcO8ZrbbitmySuw1Kg1CKId4F1uELgC3sepVRKpUlEpComMBNx\nq9iqcT9wuPVte8mWIhKbjJe9FNgKGL1i+7evevrL//wdsFNRs+XABcDfgcXlVFvIeNlGYDzwcj7M\nbYw5bClBc+ZEpFqLgY3AwAqvy1jf3p9APCJS2rPA0cC7oxaNfQX4DG4/15UFr9esb9+r5Kb5MNeC\nmzohdaCeORGpmgnM7UC2gkuetr7dJ6l4RGRLGS97LG6f5DuBXwHbASvyYa7T7R8kfdQzV8QEZhfr\n21equG5/4BBgHK7y/W+sb6+KOz6RXiZHZcmcqsGL1FDGyw4DfonbzusTwKP5MNdc36gkbloAsaVD\nTGAq+XLCBOZTuOK/l+A2ON4HV2dHpK+7g00rUlezed2453G9AABvA5+3vv1D7UITkcgA3F7Iw3Db\nekkfo2SuiPXttcBOJjBfKtXWBGaCCcxjwN+AbXDzBa7ELc++LdFARXqBaGL0mbhaidsBn8MtbrgM\nOBD4Fm67rh2tb++qV5wi/VVUIuRvuNWmbwNjknxexsuOy3jZ/TJedusknyOb05y5TpjAGFwv2wLr\n25s6OT8FV17kSjb9wVgBNFrfrq9ZoCIiIiVkvOwhwIW4odbz8mFudkLPGQT8EDfdaAnwvXyY04r1\nGlDPXCesb6317UWAZwLzfQATmEYTmD1NYK7CbVNyC5v/Dec6JXIiItILPYSb9rAE2D/jZUtXl6vO\nQNyuMKNxK2RHJvQcKaJkrhvWtzcAG0xgnsSVYZgFnFPQZBmuR+5x4NraRygiIlLSaGAibjrQybi5\nc7HLh7k1wCO4XSPGAKcm8RzZkpK5EqxvrwCeAVoLDj8BfAloBMZY337M+nZ+PeITEREp4R2gDfed\n1QrsluCzXgIGRc86LeNlt0nwWRJRaZIyWN+eYwKzEPc3jVuBueVUxBYREam3fJgLM172PlzP3JLo\nlZRZwAJgd9wK2hNw88slQUrmymR9+6N6xyAiIlKpjJcdgKt/ugrYwOYlhGKVD3MbMl72h4APvAdo\nLnkNKJkTERHp2w6MXm247bySWgDR4SHc3q7jcXPoJGFK5kRERPq2jwJP4hYm3BXVnktMPsxZYGaS\nz5DNaQGEiIhI33YPsBH4J5CvcyySABUNFhER6eMyXrYBCKNeM+ljlMyJiIiIpJiGWUVERERSTMmc\niIiISIopmRMRERFJMSVzIiIiIimmOnMiIiJSE2FL0zTgeOAFIOc1Nod1DqlPUM+ciIiI1MrpwCjg\nCGDHOsfSZyiZExERkVqZj0vmVuH2bpUYqM6ciIiI1ETY0jQI2AVo8Rqb36l3PH2FkjkRERGRFNMw\nq4iIiEiKKZkTERERSTElcyIiKWECM7CTY+eZwHy7s3Mi0j9ozpyISAqYwDwI7A9Msb6dbwLjAZcD\nF0RN5gBHWd8urFOIIlXJeFkDTATagQ3A6nyYW1vfqNJFyZyISAqYwCwBtgFeAtYCk4CxRc0eBQ62\nvm2rbXQilct42ZHAacBOwFRge+BN4EXgknyYe7d+0aWLhllFRHo5ExgDjIk+TgH2YstEDuDjwHdr\nFZdID+0P7BO9dsf9ZWUSsDWwQ/3CSh8lcyIivd9woNw5cacmGYhIjBYDbUAL8A6wFFdM+GXglTrG\nlTram1VEpPebXEHbXGJRiMQoH+ZmZ7xsgMtFNuK295qdD3Mr6xtZ+iiZExHp/XavoO1vE4tCJGb5\nMLeg4ONr9Yoj7TTMKiLS+00ts90s69sXEo1ERHod9cyJiPRSJjCDgM8B2TIvuSTBcKRGMl72WOBb\nwN3AFfkw117nkKSXUzInItLLmMDsCJwNfBnYtszLZgJ3JRaUJC7jZQcCNwInRYf2BZ4CHqxXTJIO\nqjMnItKLmMAcjEvKRlZ46eHWt/clEJLUQMbLDset5hwKmOiwBf6Eqx94TT7MratTeNLLqWdORKSX\nMIE5FreAYVCFlz4C/D3+iKSGPsGWidw7wCJgD2BX4LlybpTxsg3AD3A1CS/Oh7myrpP00gIIEZHe\n4woqT+QAfmd9DbOk3GO4nT1s9PolrmbgCFzttUUV3OsE4GvAQcCvY41SeiX1zImI9AImMBNw+1NW\n47E4Y5Hay4e5VRkvOwY4DHg6H+aWRnuWzgJWVVh7rWPBhOm2VYzClqYGYIjX2LymVs+UTZTMiYj0\nDrtUed06QOVI+oB8mNsI/LXgs6WyHrkOv8MNy04Dgnii61rY0jQct43cDmFL02+9xuZ80s+UzSmZ\nE4lJVEZiT+AZ69uw3vFI6jyI22C83JpyHQZRwx4YSU7Gy26F2wXhPWBZlNxVLEoC/ThjK2ECLu63\ngUMBJXM1pjlzIjGINkL/La6MwCwTmL3qHJKkTPQXgGq+gBuA7WMOR2os42V3AZ4FngdeB+7JeNkR\n9Y2qbAuj19ZoIU5dKJkTiccw4Njo/TTgfhOY6XWMR9Lpj7g5UpWqdq6d9B6fBnbAfS83APvherx6\nPa+xeS2uYPXXvcbmB+odT3+kZE4kHhuBZQWfRwO/N4EZUqd4JIWi3rmLqrj0uKh3WNLrcdzwKrjV\nrMtJ0V6lXmNzu9fYrDp4daJkTiQG1retuPIBhZqAM+oQjqSY9e1fgMsqvOw84BoTmIYEQpKYZbys\nyXjZSRkv+37PWz7MPQ18EsgBfwaOzIe5tXE/O2xpmhy2NH0ubGnS0HwfomROJAYmMAOAnTo5tWet\nY5E+4f8AP6vwmlMAzdVMhyOAB4B/ZLxspuNgPsy9BHwROCZ6H6uwpWkr4Du4/X6/HbY0KQfoI/SL\nFImB9W0bnZcQ+GitY5HkmcAcZQIzvujYsLjuHxUA/hZwU5mXLAD2t759Kq4YJBlR7bgf4uY5TgIu\ny3jZHTvO58OczYe59i4u7ykTvUL0/d+naG9WkRhEPXOLgXGdnN7D+nZOjUOSBJnAvICr47UYeBWX\ndP0Y+IL17T9jfE4D8Cvg5G6a3QWcaX37TlzPleRkvKyHW7U6DZdYtQNtwBPAF/Jhblk3l/dY2NK0\nK257sCe8xuY3knyW1I6SOZEYmMB8AVeoszNHWt/eW8t4JDkmMJOB5i5O3w58yfo21p6VqBfwQODg\n6DUFtwH7pda3M+N8liQv42VPAK7H7cXa0UMWAtfkw9x5dQtMUktFg0XiMYauhy5ernEskqxvdnPu\neFxvXXdtKmZ9uwy4I3phAjPC+nZ1nM+Qnsl42UZcj9fL+TD3eonmf8Yl44fj/t/RoS2h8AAIW5qG\nAh8A3vQam1uTfJbUlnrmRGJiAnMzbmPsQi3ADnH31Ej9mMA8gFt12J2vWN/eUIt4pL4yXnY4sC/w\nJVxitjVu6PvOfJh7s5vrxuHm1B6DS+rmAEckNV8ubGkagCt7MxF4CfiR19isBKCPUM+cSHyWdnLs\nRiVyfc740k242gQmb327sONARx24aHGD9AHRYobbgb3Z1DvfAOwO7Jbxsl/Lh7lOt/bLh7nluB66\nP9co3BG4RG4Jbr7nQEC9c32EkjmR+FwI3AA8BDTi6kX9uK4RSRLKqf01CLjHBOZGXBX/Sbh5bl8C\nnkkuNKmxIcD+wHDc92l79BqCK0u0MzCvbtFtbgVuaPdg4DYNs/YtGmYViZkJzPG4HSCuVy9M32IC\nMxp4GtilisvnA9M11y29Ml52Ci45fwWXwB0LnI378z4AWIlL9kfhft//Ar4abXwvkhj1zInEzPr2\ndhMYT4lcnzSd6hI5gJlK5NIrWuBwAW7/1Km4HrgncT1vY3Bbb/0ncDTwBWAkMLgesUr/o2ROJAHR\nHpvS9zyK24d3YBXXHmkCY5Tkp9YAXF24ibgkrR34IG4F6s64HWCOwv038mFgMrAO15O3sJP7pUbG\nyw4A9sPNCfxXgkWNpUqqAC0iUr524C9VXvusErn0ilam/gK4F3gbV4LmClwPnIdb+HAc8CCuiPTc\n6NhRdQg3bgcDXwPOAT5W51ikE0rmRETKFCVjJwH3VXH52JjDkRrLh7mncNusHYYrI/I73GrWNlyi\n/6toftwc3Py5QcC/6xRunAZ38V56CS2AEBGpkAnMnsBzuGG3cjVb334ooZCkTqLyJDsB6/Jh7q2C\n4+OBYcDraV8AkfGyQ4AjcAnrffkwtyHjZYcCR0bH7smHOa2OrSMlcyIiVTCBuR84pIJLLrW+vSip\neERqKeNlTwQuxRVJ/itwYtqT1jTTMKuISHVOxa1gLNfTCcUhUlMZLzsd+CluccdA4BO48ixSJ1rN\nKiJSBevbRSYwDRVc8kRiwUifEdWy+wpuBey1+TC3vs4hdeYcXBJncYs8XsQVJZY6Uc+ciEj17i+z\n3UrgvSQDkeSYwIwygZlgArNvDR73VVyP1wygt86xnIlL3t4BrgGO6WrbMqkN9cyJiFRvfpnttgL2\nAR5LMBZJgAnMgcCnge8AvwdOSOpZGS87Gbev6yTgVeCtbi+on+uAWcD6fJibXe9gRMmciEhPXIWb\nK/SdEu0MsBtK5tJoHvBZ3O9waBIPyHjZPYHjcb23b+F6vJ7Kh7llZVw7BvgM0Bxdk/gihOgZ/0r6\nOVI+DbOKiFTJ+nYFsGuZzacmGYskZhWbasV91gTmBhOYcTE/43RgBK5X7h/A34FflXntNYCPK2hc\n7VZzknLqmRMR6ZlXymxXTaFhqSMTmONxQ4qjCg6fCexrAvPRavbaNYHZDhhhfdtccHgebo7cCuCO\nfJhbVc69ohp3OwNrcUP5WlHaT6nOnIhID5jAfAD3ZTy8RNMDrW8frkFIEgMTmA/i5kR2VRh6EW6f\n1ibcEPoI4B/Wt290c8/PAr/DJV97WN8uAsh42UG4pKwlH+berSTOqN7bGbhFCd/Xvqn9k5I5EZEe\nMoFZDDSWaPZR69snaxGP9JwJzCjgz7gaal15C9iu4PNyYHpHkhbd5wxcUjgA1zvbUc7mR9a3Fxbf\nMONlDwBOxJX7uAN4Nx/m1nUXa8bLDgTaVLS3/1IyJyLSQyYws4E9SjQ7xvr2j7WIR+JhAjMQuBE4\nuYLL5uB6aucDOdwcuPuAkUCmoN0V1rfvL5zJeNnBwAXAN3FbZI0Ewug+lwI5JWvSFc2ZExHpAROY\nnYFpZTTNAErm0mU0LhGrJJmbxqb/Hi6I/nlsJ+3enxeX8bJ7A3fievlMwSvEDeOeAcxm00IMkc0o\nmRMR6Zld6XpeVaHfJh2IxMcEZidcAd/zE3rEwoL3NwI7sCmB6yjA6wHrcKVK1gNkvKwH7BWdm6k5\ncgJK5kREeuoDZbZbnGgUEgsTGAOcBfw/3KKGpPzEBObX1rcWN6zajkvQ5gO/BjYC7wKvA2/mw1xH\n8rc/8LXo/U3AAwnGKCmhZE5EpGe+gVvZeB3wHDAO9yXb4SXgKeDN2ocmlYjmyN0JHFWDxw0AjjaB\nufdQjjsVuBK3gOLsEitaOwoXW2BYwjFKSiiZExHpmYNww3En4eZKXQ5sAAYDTwOHWN+WVTdM6scE\n5iO4xQe1SOTA1YW7C5h3v3/HKda3nyzzukdwde8aUK+cRLSaVUSkh0xgbsJV8QeX2H0BOBi4xPrW\nr1tg0i0TmCHA1cCDwPW4BLwelgC7Wt++V6fnS8ppOy8RkZ57ouD9F4EAN4ld8+R6t/G40iG3UL9E\nDmBbYHodny8pp2RORKTnbgJWRu8Pwm2afi2wdb0CktKi3RoaSjasjX3qHYCkl5I5EZEesr5tZ/Pe\nua/jVhwO7DhgArN9tFJSepffsGmIvF7eA56t5AITmKEmMPoOF0DJnIhIXC7q5Nh/msAcEr1/CDii\nhvFIGaLSIH+uYwjvAZOtb+8v9wITmEbgXuDMxKKSVFEyJyISj+dxtcEKDQTuN4F5Crd362m1DkrK\nMrKOz77U+nZ5uY1NYBqAnwEHAvslFpWkipI5EZF4fJWCYdUiM4DhwOeiWmbSu4yuwzOvBpqsb68o\n9wITmOG4Ht5sdKg1icAkfZTMiYjE416g1FDZQFwFf+ldvlO6SaxuB86zvp1XTmMTmL1MYP4OvAF8\nLDr8NvCLhOKTlFEyJyISA+vbZuBw4OYSTeckH42UywRma9xep7XyLHBaNFevJBOY03E7iGSAMcAq\n4EJgivXt84lFKamiZE5EJCbRqtYzo9c7XTTbvXYRSRl+CnyoRs9aDRxnfbuunMYmMN/Alb3p+K4O\ngU9b3/7I+nZZQjFKCimZExGJkfVtaH17E12Xmti7lvFI16L5i7Ws7/ZN69sF5TQ0gZmG64ErdKf1\n7SPxhyVpp2RORCRmUT25QV2cnlLLWKRr1rcbgZ8A3W1s31OPA8cAJ1vf3ljOBSYw3wYeBbYrOvVC\nzLFJH6FkTkQkfjsCB3Rx7uRoU3fpBaxvrwPOSuj2q4BzrW//aH17awXXTaLzcim+CcxXY4lM+pQB\n9XC2oZwAAA46SURBVA5ARKQP6q5kxGBcGZOkEgip3DPRK+6FEHng6yYw43GdJ+uAV4DngBZgrvVt\nZ3Mru1oc4QEXmsA8aH37csyxSooZW96CGhERKZMJzCDckNjkbpodoPlPvYsJzERcAtbd760Ss4Dp\n3ZxvAa4E7ulYmWoCMwH4K90vlFkFfCfqVRTRMKuISNysb1uBg4CHu2kW1CYaKYcJzL64grxxJXIA\nK3Bz5rqyBrgEmG0Cc220u8MFlF7xvBXwSxOYr8cTpqSdkjkRkQRY376FK/L6CK4HplhjbSMSgIyX\nHZPxsjtmvKwpOnUkMDHmxx0I7Evnw6Yv43ae6NgR5Cxc4elXgBtwiWB3DK7unIiSORGRBO0MfAL3\npVtcW+zO2ofTv2W87N7ArcD/AJ8qOn0xcEsCj20AmouObQCGAGOLQ8TVvfsBMKGMeF6PI0BJPyVz\nIiLJ+Xn0zxC38KFQV6VLJAEZLzsIuBz4CK48zIej4ybjZfc9NDguO+OGg78LPJjA44sT+X/hVqx2\nphVYaH27EjcE21U5kpuB/40jOEk/JXMiIsnpKC+xjC3/f3tYjWPp76YAO+F+J9sDD0RDrV/BDWue\nNmrR2FOALwArK7hvG244vatrbPTcDs/RddkagDc6tvqyvp2PSzqvZsth18XWt2EFcUofpmRORCQ5\nHb1vE4C3is6tNoHZocbx9EsZLzsSOBE3tLkGWIDrKR0LZIFdgE8C21nfLsUV7C1lAfA0sB5XV3Ak\nbtjzYeBJXO/bC7g5kx1JvQWGlrjvZr141rdt1rfnAlvjEs/PAwcDfywjRuknVGdORCQ5Awvev8nm\nFf1D4ApcT5Aka2/cv/vXcInVbFxyvQq3enUQbkHBflH79jLuGQIzio5NiF5deQz4eIn7NpnADIx2\np3hf1At3QxlxST+knjkRkeQUftnvzaaJ8KuBPYBDax5RP9Q6dMOSlY3vTrTYeYAPXJgPc/PzYW4D\nrjetY2XrxKaP7TECmFrils/gFrdUYh2uB7CUQcAHK7y39HPqmRMRSYAJzDDg6IJDHq5EyYDo/SRc\neQpJ2ENr7n5x6DeHD/baGqasHbv6NzYIlxSc/gluUQQW+/q8Q1+4jM3nuHVmY4nznXma7ufKFdqL\nLVfAinRJPXMiIsmYypbzo3YAtmXTSsb3ahlQf7Z+zNo/rR2/agae/bsJzMUmMB3z2P5qsd9bN3LN\nQ8+e+LDFs+eVuNWLuNpxlapk9XJx2RSRbmk7LxGRBERbes0Gdi3R9KPWt0/WIKR+zQTmI7jh0Q7P\nAk8Aa4HjKH9ocyZuyLxS9wJHlNl2ufXt+CqeIf2UeuZERBIQbel1AlvWGCs2pQbhiNsn9WLcfEVw\nCxUOx22fVW4i9zLVJXLgVtKWa36Vz5B+SsmciEhCrG9nAd8t0exEE5hSvXfSQ9a3ofVtAHwbVxvu\nJdwihjZgeXeX4lauvkHPts86mPKTtN/24DnSDymZExFJ1lXANV2cex44KGojNWB9ex1uZ4VGNg2z\njgPmAkuKmrfg5si9jFv0sG0PH19OyRNIZlsx6cM0Z05EpAZMYI4Bfg2MKDg8n00lLr5ifas6YjVi\nAjMH2L3o8FJcD9wewOO4unPF27D1xKuUXikbAttY374d43Olj1MyJyJSIyYwhwH3RR/fZcthuyOt\nb++tbVT9T7TzxhvdNFmNqz/X2sm5n+Pmv+2KK0A8jai0SRfW43r/lgITKb0DBMDdwOe1XZeUS3Xm\nRERqZyFu+6hbcfu1Fidzn8KtepRkWVwyt2MX50cAu3Vx7hnr29mFB0xgZgC/Z9NCileBM3CrmVda\n34YmMJMpv3bc0cCtJjCnFu8EIdIZzZkTEakR69t/W9/eAXy56NR6XPLwrdpH1f9Y3y4Cbqzi0ldx\n8xyL7/c0bkj2FlwR4j2sbx+yvn2voHetrcJnnQAcU0WM0g+pZ05EpPYWAE0Fn1dY375Ur2D6qT/h\n9kpdgVugMhL3O1mLW6gwF3gO2Ae3f+ss4ALrdz43yfp2KXBqVw+zvl1gAnMbLkkr18IK2ko/pjlz\nIiI1ZgIzEbfpe4cQGKIhtfoygRmHGxZtLTo+FFjfVSJXwf2HAY8CHy6j+SPWt+Vu/yX9nHrmRERq\nbzFu3lbHBu+/pPJhOImZ9W2n9easb0sVfi73/mtNYI7DzZ1rKNH81jieKf2D5syJiNRY1PNzPW7u\n3G7AuT3t9ZHUaKG8794Xkw5E+g71zImI1IH17dn1jkHqYgNuEcWeJdptX4NYpI9Qz5yIiEiNWN+2\nAyfj5kl258AahCN9hJI5ERGRGrK+nQP8okSzw4oPmMAYE5iMCcwuyUQmaaVkTkREpPYuBOZ1c35c\nxxsTmENMYK7ClbT5OzDLBOZjCccnKaLSJCIiInVgAvNx4JFumowFDgFu7+TcUmAv69s3k4hN0kU9\ncyIiInVgffsobhuwrhyE28+1M9sA/zKB2SnuuCR9lMyJiIjUz7eArurYZYA53Vy7HXC1CYzppo30\nA0rmRERE6sT6djFuP9fOHAU8jitn0pXDgSlxxyXpomRORESkvi5j8+3dOmyPmzf3aInrPxl3QJIu\nWgAhIiJSJROYEcBIYKn1bdVbspnAHAbc18mp83HDsN2VMlkDHGB9+2y1z5d0UzInIiJSBROYbwP/\nF5fMWWA5bruujtdi69sLK7jfz4Fziw6/AkwH5gPbdnP5MuBI69uZZf8A0mdomFVERKQ6a3CJHIAB\nxgPTcAsXTgbaK7zfBcCsomO7AIcCfypx7XjgKROYmSYwAyt8rqSckjkREZHq/AZ4r4tzjwMXV3Iz\n69v1wJfYMgm8HDfMWmoozQB70XU5E+mjlMyJiIhUZyugq16wJ6xvWyu9ofXtS8A/ig7vCkwGfljm\nbYZV+lxJNyVzIiLSr0V7nlZTq+08YHgnx+cB/9GDkE4HbgDCgmM/Bq6gvIRuYw+eLSk0oN4BiIiI\n1JIJzDjgp8AQXDI2DTeUeVWFt+psOPNNIGN9G3ZyrizWt4uAr5jAzAH+B9fxMhH4J24Ydhcg280t\nVlb7bEknJXMiItLf5HBbZXWwwK1V3Gebos9vA4dZ3y6sMq7NWN/+zARmA/DL6NAewFO4hG4DcFIX\nl+4ALIojBkkHDbOKiEi/YALTYAJzEZsncgB3AauruOWaos9BNOctTncCbxR8HoaL93ngLKCz2nZj\nYo5Bejn1zImISJ9kAjMM+DhwDK5W20SgsZOm/1Vlwd9jgLm4BQoA71QTZ3esb5ebwHwc+ANupWqH\ny4Ajcb10twKDCs4VJn/SDyiZExGRvqpj54TxuJWnrbierLW4IrvXADtZ3z5Xzc2tb60JzFHAzsAh\nbFkjDgATmFG4Va97AM/ievRC69uy6tBZ375uArMfbp7fOdHhAcDduOT0k8DfgBHRuSnAi9X8TJJO\n2gFCRET6rGi7rVagCVgArCdaJWr9+L4ATWBMZ/czgZkE3IxbYfpv4LPAUuA069s5FT7DwyWgZ0eH\n/gEcGiWVJ7Jp3t9LwKnALOtbrWztB5TMiYiIxCRKHo8HJuF6x1YDf8Ft9TUCl9TdBZxebs9c0f09\n4OfACcBe1rcLouMGuAc4vKD5/cBx1rcrqv15JB2UzImIiMTABGYX4AFgQsHh2dGrATgRuMT61o/h\nWSOsb1cXHRsPLASGFhz+jvXtFT19nvRuWs0qIiISjxvZPJED2BO3PdeO0efJcTyoOJGLji3D9cZ1\n2Aj8bxzPk95NyZyIiEgPRYWID+ji9DFAHlcj7nsJh3JLwfvzrW9bEn6e9AJK5kRERHpuUDfnBuOG\nX4+Oq6BwNx6L/vkD69tKd7SQlFJpEhERkZ5bjFtFOqWTc/db3z5RoziWRLFcXKPnSS+gnjkREZEe\nisqSnIWrbVdoGXB+DUMZDHyuyiLIklJazSoiIhITE5jJuMK+k3ClSa6yvl1c16Ckz1MyJyIiIpJi\nGmYVERERSTElcyIiIiIppmROREREJMWUzImIiIikmJI5ERERkRRTMiciIiKSYkrmRERERFJMyZyI\niEiKmcAYE5iJ9Y5D6kdFg0VERFLEBGYYsDfQCvwEaAZOAS4A5gL3Wd+G9YtQak3JnIiISEqYwHwW\nuAMY0E2zK4D/sr5dYQIzGNjd+vaZmgQodaFkTkREJCVMYP4EHF1G0xej10HAKmCy9fWF31dpzpyI\niEh6/AfQVka7qcDxwDbA24lGJHWnZE5ERCQlrG//DVxT4WV3qVeub1MyJyIiki6XABvLbLsSuD7B\nWKQXUDInIiKSIta3bwP3ltn8Wuvb5UnGI/WnZE5ERCR9vgosLtGmHbfyVfo4rWYVERFJIROYM4Eb\nCg61APMLXq8Ct1nfttchPKmh7urUiIiISO91M7AMWAC8an27pr7hSL2oZ05EREQkxTRnTkRERCTF\nlMyJiIiIpJiSOREREZEUUzInIiIikmJK5kRERERSTMmciIiISIopmRMRERFJMSVzIiIiIimmZE5E\nREQkxZTMiYiIiKSYkjkRERGRFFMyJyIiIpJiSuZEREREUkzJnIiIiEiKKZkTERERSTElcyIiIiIp\npmROREREJMWUzImIiIikmJI5ERERkRRTMiciIiKSYkrmRERERFJMyZyIiIhIiimZExEREUkxJXMi\nIiIiKaZkTkRERCTFlMyJiIiIpJiSOREREZEUUzInIiIikmJK5kRERERSTMmciIiISIopmRMRERFJ\nMSVzIiIiIimmZE5EREQkxZTMiYiIiKSYkjkRERGRFFMyJyIiIpJiSuZEREREUkzJnIiIiEiKKZkT\nERERSTElcyIiIiIppmROREREJMWUzImIiIikmJI5ERERkRRTMiciIiKSYkrmRERERFJMyZyIiIhI\niv1/nJuMYuIx9CQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = protected_areas_utm.plot(figsize=(10, 10), color='green')\n",
    "data_utm.plot(ax=ax, markersize=5, alpha=0.5, column='interference')\n",
    "ax.set_axis_off()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " \n",
    " In addition to the previous figure:\n",
    " <ul>\n",
    "  <li>Give the mining sites a distinct color based on the `'mineral1'` column, indicating which mineral is the primary mined mineral.</li>\n",
    " </ul> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BChufyKotV1fk2L/cuCvMaDJ3NP/fqWPHjqlmz549MioqalRsbGzq9OnT43Jy\nctpmtT5n/vz5I/bu3etsKR1CCHEJN3A7N/C93MC3cwM3QvxyvFj92DqQAwBu4PUQtWcB4GmIBfWu\nBnIA8Bo38HU9uN4TufL7cS9EHjpnY40fIYK3CAAnIWoL10KsF/03k1l/JpEeEDwimNtVUK5NPF3C\nhiks7SY0HKaw2BNOl7DdhRVO/4DY7XZkZmbGTZs2re748eMHS0pKDr388ssny8rKOvyHZs2aNUfT\n09O7tZ3dbrfDZqMZYEJIr1oBkWYDEPnkLibFHRz/FcQU8p/Rszx7n3EDX9KD6z0Ok9lMdFw3tzP1\ncC7oboYYNZ4K8T1W45d8dEEQSwW8APyVyWykC/0ZtDwimDt06IhfMq/rNDdTCq+zHjp0xOlyNRs3\nbtSpVCq+bNmyMy3HJk2a1Gi1WtnMmTPjWo7deeedw1euXBkMABkZGYlbt271feWVV0IXLlwY2XLO\nypUrg++6666ogoIC75EjR6befvvtw1NTU1NKSkq8P//8c78xY8YkpaSkJM+aNWtkTU2NR3zvCCG9\njxv4Zogpy5chSmgtgCj+7m7FECNvF+AGbuUGvo0buBVALsRaQWet76h90j4ms6UQFS5cCaCHOHn+\nTxC1g7vyGwBFTGYbmcwMjg0ZHs0jAoLGpmaFH7N1WupCx2y8sbHZ6R+InJwcH71e3+BKv+64446z\nX3/99blFyWvXrg1asGDBWQAoLS3V3H333ZV5eXm5Op3O/tJLLw3dunVrYW5ubt64ceMann/++c7K\noBBCSKe4gZdyA3+SG7iZG/gnAK4FMB8XFrrvTxu4gVd0dZIjWe/XXZ3XxjMQlRt6q77toMdkFgPg\n/+D6SGiHy43aUQ/xwaK7FACuB/AYxJo8j+YRGyB8NN72Wq5kAZ0EdHVcyXx8vPt1PnPYsGHWqKgo\n87fffjskNTW16fDhw5qrrrrKVFRU5D106NDmK664oh4AfvjhhyElJSWajIyMJACwWCwsPT3d1J99\nJYQMbo66mv9iMlNBLDp/AOJ3ROuEreUAXoco3XQYYlpsMkRy2DiI8k4mAOEudOGso+3u8u7i9Z8A\nbIbIU/ZfSvbrkgqI77kr30/AuWoleyESVjvLDMAPQLUL1w4aHhHMpabG1OadyA+YiOoOy4PkMp0q\nNTXG6R+GtLS0xvXr11+wRdvLy4vb7b8s0TObze3u5PnVr3519pNPPglMSkpqmjVr1lmFQgyW+vr6\nnruYc44pU6bUfvXVV0faa4MQQnoLN/B/AgCT2YvcwDmT2Z8BJAJYCWA7N/C2HyS3MJm9DCAS4pd/\nCIAlAO5C1+lEGiB+iX8E4GNu7ot5AAAgAElEQVTHRocuOWqizuvgZTuARwH8hQq19ww38AYms/cA\nPOFiE12lw7ED2A7xgcGVQK7lHvdB7HD2WB4xzTohMdxUcEksL7N7tfu8ZXYvReElsTwjIczp0a45\nc+bUNTc3sxUrVpz7R2vLli2+VqsVxcXFPo2NjayyslK5bds2v/auv/32289u3rw58LPPPgtasGBB\nVXvnzJgxoz4rK0t78OBBNQDU1dUpOtstSwghPdUSCHEDX8IN/Hpu4P9pJ5A7dy438OPcwJu5gZdx\nA18KkR9uAsTI3UiIqbpUADKANwCMARDIDXwaN/C3uhvIterbVRCBYGvHAVzBDfzPFMj1mk09uLar\nYE4B8TNSha5r3G4C8FYHr3W33uug5REjcyFate2G2RMqvtyIsITTJcoUXmfVMRuv40qWy3SqwrBY\nfsPsCRWuJA5WKBTYsGFDyeLFi6NeffXVcLVazSMjI82vvfba8Tlz5pxNTk5OjYmJaUpNTW13XV1o\naKgtPj6+saioyGfmzJntnjNs2DDr6tWrS2+55ZaRzc3NDAAMBsPJ0aNHU148QshFyRFM7W5zOBeA\n1Evt5zKZXQaxM/dBx+HrulvVgXQPN/DtTGb/BzHa2ZVyiBQiCRBJfmO7cY03xKhuRwMUhwHcDiAL\nYtr2OIDnW73eDGBnN+4zqDE+wD+8ZGdnl+r1emN3zjWazMrdhRXaQ4eO6Bobm5U+Pt621NSYuoyE\nMKoA0U3Z2dkher0+2t39IIQQ4NyU628AgBv4u27uzqDDZPY7iHQwna1RtAA4BjHNbgegA1CD7k+d\ncog1k0Ftjt/T9nvq+H5Pc5x7GEBJRyPGnsSjgjnScxTMEUKIZ2AyuwPA+zh/SVYdgJ8hRt9sEEFY\nPUQeOjVEpQdnKj7YAHwHMYr3F4gROAXEesoCqtLRPR4xzUoIIYSQ7mMymwTgg3ZeyodYo3YcojTc\ncIh1b+dd7sSttkOsf3yOG7gzu5lJKx6xAYIQQgghTlnQwXENRLA2HCIIi4eo2tDcSVsdbW44hl/q\nvT7OZDbLhX4SUDBHCCGEkFaYzOYC+J3jr/txfr64tuvTFBBVG8od57bWCGArxNQpINbWcQAnHMcj\n8EvN1ych8gISF3jUNKvRZFb+VFih/bngmF+D2aLwVXvZxyYOr51IGyAIIYSQFg0QGxlaBnx2AJgC\nEaxdkFfVoR7ACAD7INbBxUAEgZMAFEKM3gVDJPdNxPmbI5oBjAWgxS81g4kTPCaYyy+vVf/zv/vC\nQutPsrFeTdYhSrutvkHBSncfDdhzKMJ/wVXjKpLC/SjVByGEEE8XCJH77ShEnDANIsga18k1yRBB\nYCouTDOS0sX9vAHcBuAwk5nMDZwGV5zkEdOsRpNZ+c//7gsb3XTYnubTYNGp7FzBAJ3KztN8Giyj\nmw7b//nffWFGk9mlYr1KpTI9KSkpJS4uLjUxMTFFkqQwm038LG7dutX317/+dVSvPlA3FRQUeK9a\ntartVm9CCCGkXUxmQwE8BZHwdxzELlVApBvp8nI4V4+1rWcApPXgeo/lEcHcT4UV2tD6kyzE22Zv\n7/UQb5s9tL6M7Syq0LrSvlqttufn5+cWFxcf+u677wq/+eYb/6VLlw4DgGnTpjW8//77x3vSf1cV\nFRWp16xZQ8EcIYSQ7joNkSD4EQDDIAKsdyE2K+wEUOY4zwzgPwBeAfADxHRqT6pFtHimF9rwOB4x\nzfpzwTG/sV5NnRb8jfZqtO4rOK6bPXZ4TU/uFRERYX3nnXdKJ02alLJixYqyr7/+WrdixYqw77//\nvvj777/3XbJkyfCmpiaFRqOxv//++0f0er155cqVwRs2bAiw2+2soKDA53e/+115c3OzYs2aNcHe\n3t72b775pigsLMy2YsWKkPfeey/UYrGw6Oho89q1a4/odDr73Llzo3U6nS07O3vImTNnvJ5//vkT\nd99999mnnnoq4vDhw5qkpKSUW2+91WgwGE735NkIIYQMbo4pzq9bHXoBAJjM/CGmUUcCeA6iJNt2\nALaW0mlMZvdBrI97sgdd6E7VCNKGR4zMNZgtiiFKe6fZkX2Vdt7Q1OzSNGtbKSkpzXa7HSdPnjwv\nWNbr9U27d+/Oz8vLyzUYDCeXLVsW2fJaYWGhz7p16w7v2bMn7+WXX47w9fW15+Xl5Y4fP75+9erV\nwQBw2223nT148GBeQUFBbmJiYuPKlSvP1YOtqKjwysrKyv/yyy+LDAZDBAC8+OKLJ8ePH2/Kz8/P\npUCOEEKIq7iB13ADt3ADL+AGPp8b+BZu4NbWNXC5gZ8F8FkPb5XEZOYRsUlv8oiROV+1l72+QcF0\nqo4DugabgvkO8e61RZftVdaoqqpSzp8/P6a0tFTDGOMWi+VcYsVJkybVBQYG2gMDA+1ardY2b968\nagBIS0tryMnJ8QWAvXv3+jz77LMRdXV1yvr6euX06dPPjSJmZmZWK5VKpKenN1VWVnr11nMQQggh\nTjBCpB6J7OrEdtgA/JUbeLtLokjHPCL6HZs4vLbUouk0cC21+KjGJUb1ypbo3Nxcb6VSiYiIiPOm\ndh977LGI6dOn1xUVFR366quvipubm8+9/97e3ueiP4VCAY1Gw1v+bLVaGQDcd999Ma+//vqxwsLC\n3Mcee6zMbDafu77lfKD9QJIQQgjpa9zATwBIB/CtC5dP4Ab+WC93ySN4RDA3MSHMdGZIBDc2K9t9\nXmOzUnFmyDB+WXxYj4v1lpWVqe69994Rd99992mF4vzb1dbWKiMjI5sBYPXq1SHtNtCJhoYGxfDh\nwy1ms5l9+umnXW5s8Pf3t5lMpl6ZOiaEEEK6gxv4aQB3AKh04rJsbuB7+6hLg55HBHMhWrVtwVXj\nKnI0IxUHGod41VkVzMaBOquCHWgc4pWjGalYcNW4ClcTB5vNZkVLapKZM2cmXHHFFbXLly8va3ve\nY489Vi5JUuS4ceOSWlKXOOPxxx8vy8jISJ46dWpCfHx8R+VRzsnIyGhUqVQ8MTExRZblS5y+ISGE\nEOICbuCnAMyCyFXXHQf6sDuDHhvoU3LZ2dmler3e2J1zjSazcmdRhXZfwXFdQ1Oz0lfjbRuXGFV3\nWTxVgOiu7OzsEL1eH+3ufhBCCLn4MZlNhSjd1dpOAB9CVIiYBeAaAOHcwGv7uXuDhkdsgGgRolXb\nZo8dXtPT9COEEEII6ZZiAN9BVIjIB/ATgGdaNjkwmZkBvE+BXM94VDBHCCGEkP7jmG69opPX/9GP\n3Rm0PGLNHCGEEELIYEXBHCGEEELIAOZR06xGk1m5q8iozSuu9Gs02xQ+aqU9OS64dkJ8CG2AIIQQ\nQsiA5DHBXH55rXrDD0fCUm0KNtdXY/XXKG01VhvLza0K+HuB0T9zRkxFUrif2d39JIQQQghxhkdM\nsxpNZuWGH46EzVap7ZP9h1gCvVRcwRgCvVR8sv8Qy2yV2r7hhyNhRpPZpQS7jLH0G2+8Mabl7xaL\nBYGBgfqZM2fG9d5TdGz+/Pkj9u7dqwGAxx9/PLw/7kkIIYSQi4NHBHO7iozaVJuCDdN4t1vvbZjG\n255iZWx3sVHrSvs+Pj72goICH5PJxADgiy++8AsLC7P0pM/OWLNmzdH09PQmAFi5cuXQ/rovIYQQ\nQtzPI4K5vOJKvxRftbWzc1KHaKy5xVU6V+9xxRVX1Hz22WcBAPDJJ58EzZ07t6rltYqKCuWVV14Z\nm5CQkKLX65N27drlAwBLliwZNm/evOiMjIzEyMjItBdeeOFclYYrr7wyNjU1NTkuLi51+fLlIQDw\n8ccf+yclJaUkJSWlREdHj4qIiEgDgIyMjMStW7f6Ll68OKKlGkVmZmYMALzxxhtBaWlpyUlJSSkL\nFiwYYbV2+jYQQgjxEExmM5jMdjCZlTKZ/YnJzGOWXg02HhHMNZptCn+VstNSF34qJW8yW12uY3rH\nHXdUrVmzJrChoYHl5eX5Tpw4sb7ltWXLlg3T6/UNhYWFuc8///zJu+6669yUbHFxsWbLli2Fe/bs\nyVu+fPkws9nMAODjjz8uPXToUN7+/ftzV69eHVZeXq687bbbavLz83Pz8/NzU1JSGh544IHy1n14\n4403TqrVant+fn7uhg0bjuzbt0+zdu3aoKysrPz8/PxchULBV61aFezqMxJCCBmYmMxCmMweZTLb\nwGT2DyazdQC+BzARwAgAjwL4L5OZSzNUxL08Igr3USvtNVYbC/RSdRjQ1VptTKNWubyjdcKECY0n\nTpxQv/3220FXXnnleRUmdu/erVu3bl0xAGRmZtbdd999qsrKSiUAXH311dU+Pj7cx8fHGhQUZDlx\n4oQqNjbW8sorr4Rt2rQpAADKy8u9Dh06pAkPD68HgKeffjpMo9HYn3jiiTOd9Wnz5s26gwcP+ur1\n+mQAaGpqUlxyySU0NEcIIR6EySwYwD4AUV2cOgNABICCvu4T6V0eEcwlxwXX5uZWBUz2V3W4ju1Q\nfZMqZVRwdU/uc+2111YbDIaob775puD06dPn3tv26t8yxjgAqNXqcy8qlUpYrVa2ceNG3ZYtW3RZ\nWVn5Op3OnpGRkdjY2KgAgC+//FK3fv36oJ07d+Z31R/OOZs3b17l3/72t5M9eS5CCCED2iPoOpBr\n4dWXHSF9wyOmWSfEh5gOKe28rKm53ecta2pW5Ko4z4gLMfXkPosWLTI+8sgjZRkZGY2tj1922WV1\n7733XjAAbNy4URcYGGgNCgpqdzMGAFRXVyv9/f1tOp3O/vPPP2uys7OHAEBhYaH3Qw89NGLt2rUl\nWq223VFGlUrFW6Zqr7322tqNGzcGnjx5UgWItXuFhYXePXlGQgghg5ra3R3oK5IkDZEkKUySJObu\nvvQ2jwjmQrRqW+aMmIqNVrNiW7XJ66zFymyc46zFyrZVm7w2Ws2KzBkxFT1NHBwbG2t55plnTrc9\n/sorr5Tt27fPNyEhIeWpp56KeP/994901s7cuXNrrFYrS0hISHnyySeH6fX6egBYvXp1cE1NjfLG\nG2+MS0pKSpk+ffoFqU9uu+22M8nJySmZmZkx6enpTU8//fTJK664IiEhISHl8ssvTzh+/Dh96iKE\nEM/yIYDmbpzHAZT2bVfcQ5Kk6wEUAdgDYJGbu9PrWHtTgANJdnZ2qV6vN3bnXKPJrNxdbNTmFlfp\nmsxWpUatsqXEBdVlxFEFiO7Kzs4O0ev10e7uByGEtMZkpgDAAPhDTCsmAQh1vPw9ACOAg9zAv3dP\nD92LyexRAH/q4rS93MDH90d/+pNjJC4PQAwAG4AdkiRd6d5e9S6PWDPXIkSrtl03JqLmujERNV2f\nTQgh5GLnCOLuAfBriJ2ZHCKoa21qq/P/BeAP3MDL+quPF4nlAFIB3NXJOT/1U1/6mxqAGYAVIu75\nyr3d6X0eMc1KCCFk8HEEcq8DWA0RyAEXBnJtXQHA4yrlcAPnAH4LYG0np+X2U3f6mzfE9HElgDcB\nrHRrb/qAR43MEUIIubgwmTEAtwAYCuAjbuAXrDvuxEtwfv3TS9zA9zl5zaDADdzGZPYYgLm4MOg1\nA/hn//eq7zimV58D8P8AVAFYD+C0JEkDe31ZOyiYI4QQ4hZMZkEAPgVwlePQK0xmmxzHNnMDvyBd\nlGM07jIA8wA86OQtLQA+cL3HAx838MNMZp8CuLXNS59wAx80S5AcgZwM4AmIwLUleH3KbZ3qQx4V\nzBlNZuVPRWe0e0tO+TWYLQpftZc9PXZo7cT4UNoAQQgh/YjJzBtiym9mq8MqADc4vsBk1gygFkAd\nxHonDYBgAL4u3vZLbuDd2jA3yP0WQBCAawA0AHgbIvAZTHQA9Dg/kEsAcKkkSSckSeo0q8RA4zFr\n5vLLa9WvbtoXUZR/KGCU2mifEVRjGaU22ovyDwW8umlfRH557aDNrUMIIRcTx+jaezg/kGuPN4AQ\niF2I8RCJb10N5ABgVQ+uHTS4gTcCmANgIYAYbuAPcwM/6+Zu9TYTgK0AjkJsirFC7HR+AMD7kiQN\nqt/5HhHMGU1m5UdbDoUlq6vtKYHcovViXMEYtF6MpwRyS7K62v7RlkNhRpPZpdqsJSUlXldccUXs\niBEjRkVFRY26++67o5qamgZdUkJCCOkpJjMNRFC1oJ9vXQSRooQA4AZu4Qa+2sk1igOGJEl2AK8C\nmAJgLwA7RHULHcQHggD39a73eUQw91PRGW2QvZYFa1i7VReCNcweZK9lO4vPOF1g2G6348Ybb4zL\nzMysPnr06MEjR44crK+vVzz00EMRrc+zWDqsJEYIIYMek5kvk9nfAJwCcK8buvAxN/AOK++Q9jGZ\nDbhE85IkKSVJug6/rAtUA6iHSJxcDeAtAJ3WNh9oPGLN3N6SU36jtHZrZzvWh2vt1r0lp3Szx0Q6\ntQD0q6++0qnVavtDDz1UCQAqlQqrVq06PnLkyNExMTHmLVu26Mxms6KhoUGxc+fOwh4+CiGEDFQ2\niJ2n7pq1+J+b7jugONYyhkIE3JMgprpnuLNPLhgDMfJrh1hnuRzAwwCOAVgoSVKFG/vWJzwimGsw\nWxS+Q9DpBgdfFXhDncXp9+PAgQM+er2+ofWxoKAg+9ChQ5utVivbt2+fNicn51BYWBhtsCCEeCRH\n+pHn4L5ArhbAbjfd+6LDZDYFQBmAY9zArUxmagD/BxH8LIaYtWtZdtTEZKbmBm52T29d0gTxLEoA\n9ZIkfSJJ0qcAbI7p10HHI4I5X7WXvcEKpvVCh7llGqxgvmovpwMuzjkYYxe06ziOqVOn1lIgRwjx\ncH8AsMyN9/8bN3CPXevCZKYDcBtEPr8dAJZCrB8rZTJ7EWLX5wMdXK6BSAPzUT90tVskSRoBYASA\ng5IkVbVzSi6AP0Osj9vtuGZQf/89IphLjx1aW5RfFZAS2PH/zMdMClV68tALchp1JS0trfHLL78M\nbH2sqqpKUV5e7q1UKrmvr++g/BRACCHdwWQ2GsAf3diFv3IDf9KN93c7buB1TGaTAEx3fLWIhkhL\n0pVFuAiCOUmSFI6+PAuxgaFakqQxkiSdanMeB7DfDV10G4/YADExPtRUpfDjlU283eetbOKKKoUf\nvywu1ORs25mZmXVNTU2K119/PRgArFYrFi9eHDVv3jwjBXKEEIL7IEaB3CEb7h0RvJj8BsA/IFJ0\nOGsik1lKL/fHFYEQ5diCIX6mQiDSq3g8jwjmQrRq2+3TUyvyzAGK3LPMy2ThzM45TBbOcs8yrzxz\ngOL26akVriQOVigUWL9+ffHnn38eOGLEiFExMTGj1Gq1feXKlSf74lkIIWSgcKyVu66XmrNBpBb5\nLURg8hyADx3HcwBkAkiGyF33G4jM/wu4gTf30v0HNG7gVm7gvwYwCmJXpzMYgMd7vVPOqwFwCGJN\nHIeo6PGzW3t0kWCcD+wSZdnZ2aV6vb5bGb2NJrNyZ/EZ7d6SU7oGs0Xpq/aypccOrbssjipAdFd2\ndnaIXq+Pdnc/CCEXPyazRAA7IfJ8ZQE4AsAPYnSoBCIj/xQAUyEqErTHCuDvAJ7jBn7Bh2QmszEA\ncilo6x4mswwAP8G1wZz53MD/1ctdcookSSoA4yDqrW6XJGmjO/tzsfCoYI70HAVzhJDe5qgIkQQg\nDUAixDRaEIAwABI38B1u7N6gwmT2HwBXu3h5CYDR3MAbujyT9CuP2ABBCCHk4uVI5pvr+CJ9q7EH\n18ZCrIF8tZf64hJJkgIBpAI4AKBZkqSePNOgQMEcIYQQ4gEcI6AjetCEHcAnvdQdp0mS5AfgegCP\nQuxmtQHYKknSa5IkedTu1bYomCOEEELcYMX82QoAV0IESdvqksdzAGpJkmr76JYcYt3iGBevVzja\n6HeSJHlBbHhJh9jFesLxXzuAaehGKhJJkhjEOk0AKBpMCYQ9KpgzmszKnSXl2gPHjvg1NjcrfLy9\n7WnDY2oviw2nDRCEEEK6RZIkDYAoACclSXJp/diK+bMZgNcgFvKbzL66LeD2m8EUGkmSvgGQ6ciX\n1mu4gXMmMwNE4CO72IwWwOne61W3BUPkxQuBiF0CIXYxMwBbu9mGAcCDECN6/wfgT73eSzfxmGAu\nv7xWvW73zrAYXTG7MrrWqlPbbHVmJSsy5gasPhrnPzfjsoqkcL+BVK6EEEJIP5MkSQfgnxAjPH6S\nJB0G8BiAHU6O9AwHcAOAYDtwCRSqOGVtDWz+gQzALIj1acWu9tORFuYJiN/zf3EkDh4Psbt4s6vt\nAvgHk9k1btgEcQYit5w3xOhgHYCrACidWDN3neNaFYDLMYiCOY/IM2c0mZXrdu8Mmxq53z4+8qzF\nX2PjCgb4a2x8fORZy9TI/fZ1u3eGGU1mZdetna+8vFyZlJSUkpSUlBISEqK/5JJLRrf8vampyV11\nCAEA6enpiTt27PABgClTpsSfPXvWI77fhBDSh6ZA5GobDrHbdiKAbwA85JjG6y6d48vLxpTM6hfI\nbBpN6+udTmLfhgTgRYgRuB+ZzA5AlLZSQqw7c9UUiAoM/S3G8QWI0bihAH7l5OaH9wCYAdQDeKt3\nu+deHvHLfWdJuTZGV8zCdZZ2PzWF6yz2aF0x21VSoXW27fDwcFt+fn5ufn5+7p133nlm4cKFFS1/\n12g0Lg+RWyy9W0Zu27ZtRYGBgYNmfQAhhLiJL0Qw0TKzxQCoIRIVezvRTigciW/tGh9u9/Hl8PIG\n7HYOIFuSpHJXO8hkNgHAr1sd0kMEoL01wPAYk9ncXmqru4bj/Jil9fq3bpEk6U0AIwFESZL0eS/2\nze08Ipg7cOyIX3xIbaclTBJCaq0Hjh/R9eZ9n3766bD4+PjU+Pj41BdffPESADh48KA6KSnpXFmU\nJ598MnzZsmVDATGS9vvf/z5i/PjxiS+//PIlN9xwQ8wdd9wxfMKECQlRUVGj/v3vf2tvuumm6JiY\nmNSbb7753I6kW2+9dcSoUaOS4+LiUpcuXTq0vb6EhYWNNhqNyoMHD6rj4+NTb7755hFxcXGp06ZN\ni29oaGAAcODAAfWUKVPiU1NTk8ePH5+Yk5Oj7s33gxBCBjJJkiZBjHYFQVRRsEIEZFYAxyRJcmap\nzjEARzjQaPELskHlzVrFWpU97OrvIIKfviQxmfXnUq29EKlIuOPrOIBPJEmKkiRpniRJid1pRJKk\npt5ei3gx8IhgrrG5WaFT2zr95mm9bbyh2flp1o58//33vp999lnwvn378nbv3p337rvvhu7atcun\nq+tqa2sVWVlZBc8+++xpx9+Vu3btKnz++edP3HzzzXFPPfVUeXFx8aGcnJwhe/bs0QDAq6++euLg\nwYN5eXl5h77//nu/vXv3ajq7x5EjR9RLly49XVxcfEij0dg/+uijAAC45557RqxevfrYoUOH8l56\n6aUTixYt6ut/DAghZCCZCpGnzQdi/VYDRDmpNRD517rtkTUbSwDcYfPW3M0DgoHzE/j79rCfyT28\nvjtGAXiNycyZ0UiXSZJUA+AyiPd5EcT6t3kQO1xnA1jqWM8ISZLCJUn6iyRJz0mSNKQ/+uduHhHM\n+Xh72+vMyk6Hl03NSubr3Xs7Wn/44QfdnDlzzup0OntgYKB91qxZ1d9//32X07i33XZbVeu/z549\nuxoAxo0b1xgaGmpJT09vUiqViI+PbywuLlYDwN///veglJSU5NTU1JTDhw9rcnJyOg0ahw8fbs7I\nyGgEgLFjx9aXlpaqjUajMjs7Wzt37tzYpKSklAcffHDE6dOn++V/UkIIGSC+BXAQwFmINW3eAMIh\npvucLif2yJqNBxtjR22CQtkMpZJDoQAUCsCJ6VBJkgIlSQprczjY2b64aCGAz5nMOh1A6C2SJFkh\ngrdoiAD6Koh1iyMgpk+vliRpBEQN3/sgpr5v6Y++uZtHBHNpw2Nqi4x+nQ4HFxr9VGlRMXW9dc+O\nyqR5eXlxu/2XpWtNTU3nfQ+0Wu1569pa1t0pFAp4e3ufa1ShUMBqtbIDBw6oV69eHbZ169bCwsLC\n3GnTptU2NjZ2+g9B63aUSiWsVivjnCMgIMDast4vPz8/t6io6JAzz0wIIYOZJElZAO6B2ASwGkA5\ngFqIkTqXAihJkpoB/LHN4ar2zm3n2qWOPpRJkrTPkVS3v12P/hkJbBEN4DaI3b7jABRBpEsZC7HB\noRiiJJwGIo1JTzeSDAgeEcxdFhtuOlIXx8vrvNp93vI6L0VpXRyfEBvWa9/0mTNn1m3atCnQZDKx\nmpoaxebNmwMuv/xyU1RUlOXMmTNeZ86cUTY0NLBvvvnGvyf3qa6uVg4ZMsQWGBhoO3r0qNfWrVtd\n+p85NDTUFhoaavnggw8CAMBms+Gnn37qclqYEEI8iSRJZkmSCgE86fgqAPAORFDhqpcgcqBVANgB\nseatOxZDTPcqIBIBl0qSFNP5JX3i4X5cP1cPMQ3dBBGo/R0i+FVCBHWtN6YoAVzST/1yK4/IMxei\nVdvmZlxWsW43wqJ1xcqEkFqr1tvGTc1KVmj0U5XWxfG5GZdV9Gbi4JkzZzbMnTu3cuzYsSkA8Jvf\n/OZMy9TmQw89VJ6enp4cFRVlTkhI6FFNucmTJzfEx8c3JSQkpA4fPtycnp7uckC6Zs2akvvuu2/E\niy++OMxisbB58+ZVTpw40eNr3hFCSFuORfSfOr46OicQwF8hpgFfkiTpP5209bzjyxlbIUaqABG8\nBEAEhf3tTgCFEJtD+loZRAB3DYCfIEbi3gGQ0c65TQAWQCRnHtRYR9OBA0V2dnapXq83dudco8ms\n3FVSoT1w/Iiuodms9PVW29KiYuomxIZRBYhuys7ODtHr9dHu7gchhFzsJEl6GCInmwqi/NTlrqQc\ncQSFSyGSDB+HCF6iAXwH4G6IkTwGsat2uczkW/BLTrb+8hY38Pv7qnFJkuIg1ifuhxidS4V49mAA\nJyHqtbYMUFkgNqrUQQTbawEclySprK/6524eMTLXIkSrtl2vH15zvX54jbv7QgghZNA7AZFGg0EE\nIK4ubbofwL0QSYajAcAUxloAACAASURBVKQA+BpAEsRU658hkgSXAXgZ7ln0/11fNSxJ0lAAj0Os\ng9sD8ZwPQpRUKwFwLX55bzlEQuA/AfCHCIAfAGCSJOlxx67YQcejgjlCCCGkH62D+D2bDmBND0aG\nvABUQ4xCcYjpVH+IUTqbJEmlaJUkWJZdLbvaI48ymf2LG/pkus8H4n00Q+xevR1iB7EKImGzDiJN\njAZi6nWpI+ffcUmSfguxtk4DsdaOgjlCCCGEdE931tV102qIRf7PQQQmCgDvA9jTQT1Yd6yfSodY\nG1jaB20fgUhJMhLAdgDTIKZSLRAjc9EQo59rAdzT5j15AyIPXTbEzt9ByaPWzJGeozVzhBDS/yRJ\nUkCk3rgMIqC5z5F37QJMZiUQgU9/2g9gXG+NzDnq3DIATJIkW5vXZgJ4BmKU7a8A/AAYAfzsZK3W\nQcOjRuaMJrPyx5JK7fZjVX6mZptC6620Tx4eVDs1Npg2QBBCCLloSZJklySpZcH/2Y4COTf6S28E\ncpIkeUOscRsLEcyZJEl6VZKk/Fan1UCsm+MAxkmS9Oee3neg85hgLr+8Vv233UfDmv28mH+0zhqq\nVtrMZhvbXFkb8N13lf6/yxhRkRTu50xdPUIIIaTfOKYPz7i7H+0ohJju7BFHOa5nAEyHqF2bCmAL\ngCsA5DvOmQ+xySMAwDaItXAezyOCOaPJrPzb7qNhXpFae6DO+9xcukaj4poIncXk16z42+6jYYbL\nE046O0L329/+NmrEiBHmllqqU6ZMiY+IiGhes2bNUQC49957IyMiIiySJFW0vbagoMB79uzZ8S2V\nFubMmRNTUFDgc9tttxkNBsPpnj31+ebPnz9i2bJlFenp6U2PP/54+B//+MdBu3aAEEIGA8dUYyjE\n2jB/ACcuhhE5xtmmqZhaGYjAoQdw4KfD7PC7EJsxeupvAG6ESPYLAEchSqbtanXODRApWGxwbAyR\nJOkuiITLP0qSVN8L/RhwPCKY+7GkUtvs58VaB3KtaXXe9gqdSrmjpFKbqR/m1E6XyZMnm9auXRsI\n4LTNZsPZs2dVJpOp5QcRe/bs0d56661d/pAfO3ZMtXfvXm1ZWdmBtq9ZLBZ4eXk5060LtASXALBy\n5cqhFMwRQshF7xaIFBzhECk5KhwB3g4Anzg2WHSOAwooYGft/vpzxYEn8MQ2L3g9A0AzBmPGg+Ot\nbvWla2MhAlcG4N8AXgHg3SadyOcAZkEEt9cAuBqAHWI36/8BeKEX+jHgeEQ5r+3Hqvz8g306/TTj\nH+Jr/fH4WZ2zbV9++eWmvXv3agFg7969PomJiY1DhgyxnTlzRtnY2MhKSko0EydObLj//vsj4+Pj\nUxMSElLefvvtwLbtXHnllQlVVVVeSUlJKZs3b9ZmZGQkPvDAAxGXXnpp4gsvvBD2z3/+03/06NFJ\nycnJKZMmTUo4fvy4CgCWLFky7KabboqePHlyfERERNo//vGPgIULF0YmJCSkTJ06Nd5sNjMAyMjI\nSNy6davv4sWLI8xmsyIpKSklMzMzBgDeeOONoLS0tOSkpKSUBQsWjLBa3f7BjxBCiBilCm71dTVE\nvrqrIeqOdkrBFZiESZiN2Yjlsb3SoTgeZ/GC1/MQaT4UENOdDwCAJEmpkiTd6cgL54r3IFKw5ABY\nKUlSYzt54bZApCMBRNCngBiY0gF4WJKk/t74cVHwiGDO1GxTqNXKTj81eHsruanZquzsnPZER0db\nVCoVLyoq8t6yZcuQyy67rH78+PH13333nfbHH3/0TUxMbFyzZo3/gQMHfPLy8g59++23hc8++2zk\n0aNHzxtq++qrr4qjoqLM+fn5uddee60JEHVX9+zZUyDLcsVVV11l2r9/f35eXl7ur371q6rnnnsu\nvOXao0ePqr/77rvitWvXFi9cuDDm8ssvry0sLMzVaDT/n73zjo+rOtrwc3ZXq27JVe42bti4YDCY\nYmrowfQWAsS0JAQIEAgECLBzIckHIYROCCEJDiShd9NDB4OxTZHBNmDci9zU++6e74+5wrKsspJW\nctF5/NNP0u69587K0u67c2beiT/++OObzX697777VqampsYXLFjw1fPPP7947ty5aU8++WSP2bNn\nL1iwYMFXgUDA3n///W0aGO1wOByOpPKy/3k9WvT/KpqlW0nzfmkrALrRjd70ppxyRjIyKQGNZvRI\ni234WvmliByAdrQ+hPq7/d7PIraG24HdgQNEZGNjB4jIOnRMV0PqhN2erbzmDkGX2GbNCgfj1dUx\nk5YWalLQ1dTETFY41KaO1kmTJpW99dZbmTNnzsy68sorC5YtWxb+4IMPMnNycmKTJ08ue++997JP\nPfXUjaFQiEGDBkX32muvsvfffz9jjz32aLaF+vTTT//+l3nx4sXh448/fuC6detSampqAoMGDfq+\nWePQQw8tTk1NtZMnT66MxWLm5JNPLgEYO3Zs5eLFi8PNXeOVV17JnjdvXsauu+46BqCqqirQp08f\nl5pzOByOrc90dEs1BMxHa8kGAGtFpKaZ8z4CDiijjGKKySGHhSxMSkCllGZbrDV8r9Ms8Ac/xiCb\nBtxfhs5QTbgxwt+qTaTU6cfoBIz6r+kWbYiYnej1diS6hJibMrhHySsbSnLTBmTXNnVM8fqK0NGD\nuhe1Zf199tmn7MMPP8xasGBB+p577lk5bNiwmjvuuCMvKysrds4556x/4403urVl3ezs7O+LHC6+\n+OLBl1566Zozzjij+MUXX8y+8cYb+9fdl5qaagGCwSChUMgGAppwDQQCRKPRZt8ZWWvNKaecsuHe\ne+9d2ZYYHQ6Hw9Ex+OLm63o3RdGmgJa4FhgZNdFj37HvBMOEqaadZg2+bCqggBixWIBAnXAz6Fit\nurFldZ/rmjaSjoi8IiJT0HFmk9GpEEuBa53P3A7M/sN7lr355oacsm41gaxGmiDKSmsC4dKo3XfP\nnmVtWf/AAw8su/fee/sOHjy4OhQKkZeXFyspKQl+88036f/617+W1tbWmr/97W+9L7744g1r164N\nzZo1K+uuu+5aXllZmfA2d2lpaXDw4MG1AA899FC7tkFDoZCtrq42qamp9sgjjyw58cQTR1x77bUF\nAwYMiBYUFASLi4uDo0aNau5dn8OxzWI8Y4CBQCa6HVPLJjuHCcBJ6BDyvugw7pWoQ//bNmJdVtqx\n3WMjNgacaDxznTX2pvYKuZ62J3uxF2mkMYABxNnsZdTU+2z9jyjwCPBVuy7cDCIyU0S+BPZHPecy\n/et2SbqEmOuVlRq7aPKQgntnLc0ryA4Fc3plRMPhoK2piZni9RWhcGnUXjR5SEFbjYMnT55cWVRU\nFDrxxBM31N02evToyvLy8mC/fv2iZ511VtGHH36YNWbMmLHGGOt53orBgwdHFy5c2OwWaH1++9vf\nrjr99NOH5+Xl1eyxxx7ly5YtS235rMY544wz1o0ZM2aXcePGVTz//POLr7vuupWHHHLIqHg8TkpK\nir3rrruWOTHn2I6ZgNbu1KccqAG2aD7yOQ9YbzyzALgLeLKDZkw6HJ3Jp8lYZDjDySEnvhM7lQcI\npAAb0L+ldDaJOfyvS9Aav7ki0lhtW9IQkRIR+RswBXhdRJrcfdvR6VLjvNaXVQc/XLQh673lhdll\nNdFgVjgU239Q99J93QSIhHHjvLYexjO90e2TGTZi39ja8WyrGM8EUM+pFrv9msEDPCfoHNszxjNB\ndFbqwPasM9qO5giOiOeSW4XWw5UDZwMPoj54dYKuLitn0FmyB4nI/PZc25EYXUrMOdqPE3Odjy9O\njgMeQ00yAf4CXGwjNmnmUTsKxjPPA8ckYanrgd87QefYXjGeyUEnKdSv294bmMnmGbXvybJZhAmz\nkY3fH5FhMziFU74bytCeqJ/bIuB0f90Z6KB72FQvV/f1SmBwkjzoHM3QJbZZHY7tnBTg32wScgC/\nAAYZz5xrI3ZbHO+zVTCeGY0aiiaDm9CautuStF6XxnhmN7QLcSbwFtAfKLMRm0hBv6NtlKCiawFw\nADDQRuzHxjNfAzs3PDjX5rI/+5NKKutZzwK7gAIKvq0wFXf3tD1nAKcAe6H/f6tFZIWI/AUdr1Vf\nxNV93R84EXiquSBFZBDwezSbd4OIlLTzcXc5dgQxF4/H4yYQCDjl38HE43EDuExQ55NH43+rg9An\nPwdgPJONusMn83mt1d6Tjk0YzwwHjkRf0H/QyCErjWdG2Yit6NzIugZ+Vvkl/9vv6t01m0bEXBZZ\nhAjRi14MZjB7smc8SHBeqk19XETWADeLSFBE6pcl3YF2lE5FRVzd31+doHtURH4kIo0KOt+L7kl0\n+oNF30Bd06YH3IXZEUyD561bty7HFxqODiIej5t169blAPO2dixdCb8z83igtMFdy4Bz/a41h/Jr\nYEwS14sDf0viel0G45lfGM98AHwL3EPjQg7UM+2KTgvMUccstGxjLLBL3UeM2O596HNTD3osyiSz\nMo202lRSj0JHh2UDNBByiEiNiJyM1s5dyebPVXWec38VkeZmUvb3jwsB40UkLTkPs+uw3dfMzZkz\np08oFHoQGMeOIU63VeLAvGg0ev6kSZPWbu1gugrGMzcB1zW4OQYMd9tTmzCemYJu/bRviPHmPGgj\n9qdJXK9LYDwzAvimFaeUAyNtxK7uoJAcDTCeSbER22jnp4jsik6e6Fvv5irgWBFptvFKRMYA/2tw\nbh1/An7TWP2ciPwRuAgIo78PzwK/EpHCejEHgGBTcXd1tvttVl9YHLu143A4OojGxMmbTshtwQjU\nLqGxF5G2sBatS3S0nkGtPD4TOBetmXL4iEguunW5EXi1YUasPbQgiEYAPfyv67zjAui2bEtd9AuA\nX6HTH0JopjzDv+8SYKD/uH4vIh/UO+/vwAVodi4V2BUYAhTWO+b3qDHw/S3E0CXZ7sWcw7GjYjwz\nisa3oB7p7Fi2dWzETjee+RdqKXIIaksykiY69hJgrTMQbjMT23DO5KRHsf1zCmqIGwDWAHM76bpv\noaJsAirk4mi2rMXMqZ91e8z/QERuBS5nkyg8Gd1Z6Cki+9XzhRuK1sqFUV3y+Qu8sNHzvCz/2qPQ\nusuNxjMP24gtT85D3XFwYs7h2AYxngkD/6Txv9GXGrmty+MXe9/gf2A8Mwnd8gmh2Z/WcFNyo+tS\nNFUf1xyTjWeMs4HZjHI0UxWj8cHyrUZE+gFnodm+Rxoz9RWRjSKyG5oVvB7NkC1At1lfE5HWTEq6\nBrUy2Qdt5NqZTfNb62caPwG+RN+APX4jN86wxs71jylBrVB6Af3QOsv6I84cuBozh2Obw3jmAOAZ\nYN9G7o4BbZoh3NWwETsHdamf0obTX05yOF0C45k04KA2nNoXfZF2bOIp1E/yNiBZxrvHo/NMD6KJ\nDKqIDAF+hjZFXIq+ecwDTgBeE5GEx0mKSFREIiJyOPBH1MD4O+CnIhKvd9xG4HBgnIhcYY0dCvQE\n+qDbvkegW7/TbcQ6IdcILjPncGwjGM/0Q58w723msFfd9l/i+Jmez41nLkO7XRNxwn/cRmzD7mFH\nYkwAPgJeQJsg7gcGJ3juaGBFB8W1TeM3DlyIzhi9S0TKRaQaeD/Jl1qOZsmq0ZFbDeMYBPwB9ZJb\ngtY/3ok+L0XRzNlY4N2mLiAiWej/+XcNMn//QWvuSkVkCysaEYkCxcYzfdi8XtUCi9FO2ecTfJxd\nDifmHI5th3vRJ82msDQv9BxNYCP2TuOZv6EZiZuB8Y0c9jRwqY3YLikokoGN2FnAYXXf+13GH5FY\n1m1oB4W1PXAsulM2xv+YnayFx08f3xNtKijJHJj5bs/aif02dJ+csiRv95hsefiuaH1aAM2ErUbr\n9Zaj/z8bgVUi0r1+p2kdvqXInWitX4GIXAHUAl+KSA06Zq9JfCumfwB7+DeVAj+3EfvfVj7sLofb\nZnU4tgGMZ3Jp+cWswkasq5drIzZi635+U4DzgFfRbrkqNANyphNyycX/eZ7F5vVRTTGkg8PZlpmL\ndn2WoMIpKez2z90ONdb8C3gNuKsspeLaeQPHXrIyJ+2yYLTyxqEz/vP9/GLfvPeHqGArRLdF7wTS\n0e3OADq+6wPgYxE5pZFL5qA2YRYVhs+inapXtRSrL+R+Axzt3/Q4MNEJucRwYs7h2AawEVvE5g7t\njeGERhKwEVtqI/YfNmKPRAuqR9uI3d9GbOXWjm1HxEbsW8BptCxSurKYewNtFrhGRJrNXiWKiOT2\nL+9/fVZN1m6BeKAb0AfsMBvIsN0rTY9+RSuPGbfklSfHTx8/tt5pG9Hs2UfAi2waZ9cdtUnqhpoD\nD9NLSL8Gl12LCrhsNBvYF63N+7Vfi9covpC7EB0LBjpV4kwbsS09Jzp83Darw7Ht8C5wUjP313RW\nIF0FG7HVqHeVowOxEfuU8cwMIIJmXxpaxlSjAqJL4lt6rEnyssMGlw0uLOteVpoWTeueEk+xsUDs\nnrQN7xzXIzrpxKrYe5kxWz4Gy9Ei8hWwH9o1+j7whYiUiUhfdMwWbK4XAqhQa/gGKNP/WAgcyCZL\nklS0tGGLvzXjmUHo/33/ejefBDwHvN2eH0BXwok5h2PboaU5oG5OqGO7xUZsFXCN8cwf0LqsEWjG\nJx2Y4boUk4OI9EKF1tK8qrz56evSw8szlo9OsSkTQ4R+Hjfxc2rNh3kF6eunFqZVVWAwaFPD31D7\nj/+JyGn+cpZN3m/1BbhFs3gNxdwQ1H5kVIPbV9FgFKTxTG9gGpqR69/g+EHA7cBuxjM9gWIbsVHj\nmR42Yt086kZwYs7h2HaobuH+ZI6qcji2Cn6n8Bz/w5EkRGQUWg96jP85DXhyZt7MjenR9F5AtFtN\nt+GLchf1MNb8EQhYrAXeA4ajgioFOE5ELgbuQ7dNl6LWJPXLsuJo2UfDWshd0OaHPv73FlgHnCwi\nS+ofaCN2nfHMaGCnJh7SIr/Dfy5QajzzLJolPKyJ47s0rmbO4dh2eJTmzUE7ywHe4XBsR/h2IL9G\nGxj2RzNsWcBpARuIloRLFpellFUsy172NrDhi7O/+MIaezWG64GZ6NbqOlQTxNF50Gf627+XoIa+\nNagB8CrgKzSjOrBeDONQW5Pu9UKzwD9E5NMmQm/OgPgI9DmvL2qJciVql+JoBJeZczi2HfZAn1Cb\nmm3ZpLeTw+Ho0tQfu1WICioDBMcUjXnw47yPs9Hnls/yp+VHAfKn5S+rO1lEpqBTGAwqBKuBq0Tk\nV6iIW+B/POafcgkq6qYC94hIqn9bGpvKQSzanfvnZuLO8T9/jHoSrgIeRjN7Wf5HHZ+jM18djeDE\nnMOx7bAXzQ8pd4X6DodjC3yT4T+htiD/AZ5Amw42DKwYuPrBaQ9uYT58xf/dkpqTseEHQ6pXe+n0\nGVBB9ktGM19RtE5uENqVCrAnKhRDwEPAt+iW7CL//hjqCbeQTR51AX+dKSLygog0Zk8zwv98sY3Y\n2QDGM2ehGT9h0/PheuB4N5O1adw2q8Ox7XBoC/cnu9vN4XDsIIjItyLyLLplmo8Ksw1opq7hsSdE\nMS8dU/nGCwdFP9zjmPAr/WqCsTOtZvQWoh2pdRm2usaHTHQc2F9RK5XfAa/460VRM24BjkQngFSg\nGb5bget8H7vvMZ4ZiXbQvo5m/QCwEfuajdh/AO/4N8WAU2zELmnbT6Zr4MScw7EN4Lfn79HCYV92\nRiwOh2P7xR+V9RvU7+0Sf+5p/fsNMLUqHOrVI1YaqCLNZNkaounxcBQTAyahQm4WWsNr2byTNRs4\nFdgbzbzVrbtORN4XkXzgbvTNZwqqM85BrUoAMJ4JovOnQRsazmjkodRtwb5nI/bt1v8kuhZOzDkc\nWxnjmf7oYPeMZg5b6Fs7OBwOR7OIyAfATcBQETnbb5Cou88CS3qVleW9lLZfvDyYZl/J3Itl6QMK\nQ9gi4FO0vm4j2oAQZVNNXima7bNo/dp/RGS3BtcOoGPA/oPOVO2O1tL9QkTqOvInoXYodYw1nkn3\nzYMxnhmDmhODTq9wtICrmXM4thLGMwHgfOD3aNFxc9zR8RE5HI6tjYh0Ay5Apy3cLyJtnfxyEJts\nPDYAL4jIBODngEmx8bdXlQ4Z8lDq8FpbHVg3umjtOqMjtIYCxWhmbH90Vmwl2iBxDWo/crZ/fxlw\ngogs9r9fBpwC/Aj1m/sEfW5biG6XdvNjaegV90t/zf2AL9B5rnXec07MJYATcw7HVsB/B/p39Ams\nJVYA/+zQgBxbDd9ra2+0vug9Nx+2yzMRmIBucR4JPNjGdYrQDBpAsZ8xuxv1jAN4LQif9aiOPiAi\nG0XE+Fk7RORo4AR0e/Vl//iFaOPDN8DaOPHzNqRtyLXYDX2q+vwO7Tx91o+9ABiNird/oA0R77BJ\nxNU2Em82KgS/sBH7rfHMSWjtXVO2Jo56ODHncGwdTiMxIQfwJ3/slGPH5Di0eBy0eH3/rRiLY+uz\nEs2EpaACqq18yCYft3w2vd7H0RKrO0Wkrhu1bvu1jmJUCFr0TefXwHoRiY6fPr4HsJ+Jm/SADQRS\nbMpBUwqm2Nya3FVoN+3jaI3cg8AM4FhgAFBS7xrL0Sze4AYxV8D3NXW3A4/ZiI2342fQZXBizuHo\nZIxnQsCNCR5ucY0POzqZ9b7ez3gm25+S4OiCiMgiEfktai3S5iytL5w+r3dTjYhcC5wOvFlfyDXC\nh6gVCcDnIlJfUE0BdrEBu1OMWFnMxtYUhYvW5NbkAjwlIvPx/eBEZAhaG7ca9aR7GcBGbNx4ZjWb\ni7nF+G9qbMTGcG9qWoUTcw5H53M06mieCE/YiH2jI4NxbB2MZ05Ah48f1OCukbhpH10aEVlb7+u6\n7cco8KTfrdos/hvG69Ds10topi/Hiv0A+MA/JsVGbGPbnfjirantzaV+LEuANRg+m9N7zn8e+vVD\nje0elKLNFH3RLF193ke9Net4zEasxdEmnJhzODqfU1tx7P91WBSOrc0ugNfI7bvhxFyXRkQy0UxW\nNWr/cTC6NTpIRJYBL4rIFv5xxjMD0dms56BGv/VZYDyzJ7rNej1wvvFMGdpwkI+OE6wGQjZi5zcV\nW/60/C/GTx9/PRDIn5a/vJnHMATdcu2Bbrk+2eCQWQ2+d9noduDEnMPR+UxO8LjV6BOtY8fkMdQ+\nwjS4fdVWiMXRyfgNCXWebrN94906foiKuQCbRE8O2u25DrUx+mv99YxnzgXuRW1AGmM02lAwnE2T\nFXqh3avHAr/1b7sLuLR+Q4QfbzqwE7A8X/JXJvAQ9wZ6oiLtcBG5pcH9DU3Qf2k88w8bsc4cvQ04\nMedwdCLGM6lsWfTbFA+74t8dF79j720061JHNfD2VgnI0dnsDVzkfz2dzS04ylGRZ4GP0E7QwcBJ\n6Ot2YwPqP6dpIVfHQS3cP/9Me+YCEXkHSBOROcAtaO3ebUA/YKGI/B9a61mJdq8uFZElIpKGClHQ\neaur0TmrdzVyrfeAO4FL/e/7AouMZx62EXtBC3E6GuDEnMPRudSg70gTEXQFHRyLY+tzBJCLGqvm\nAtk2Yiu3bkiOjkREhgE/QcVQAPVfa2gY/jpqLVIDzBWRuIh8jtapdUP924DvbY4m0PxA+0TI/5H9\n0f7DGT4dnY06BJ1K81PUSiSIPidNBI5Cu257ofVzC0XkcmAfVHCCdqYejIrCLcSnjVhrPPNVg5sz\ngJOMZy50b2RbhxNzDkfnsj+JCblitN7EsQPjF6Cv8z8cXYNT0SxUFirKVtLAGFdEatGO0vrkofWU\nix/ggZjneRcA01AB1J+Wjcdb4vGd2bkMtUPZHd3+N6iIq5vTOrDe8ePRzOEGdFrDzei26jBgEVDl\nbx03lkXEeKYbOsu1IdloBjCRrVyHjxNzDkcn4b+DvimBQyuAk5x5rMOxQ/IdOlWhHHhURJqtkRw/\nfXw4LZo25dDAoTeF4+EeVVStrqV2fKpN7V1t2mU/GUMzg8WogLtHRGIi4qH1nPezuairX9tZN6/V\nohnlauB4NEu3AJiDbqNugfFMBro9W9fp2q/BITW4utFW48Scw9F5TAAOaOGYjcCxNmI/6IR4HA5H\nJ+C/kZsEfBkh8hRa31YkIomUUhyTGc08pyZQMzoYD5YCI/Zir95BgnxuP2epWdqWkD4HzkK3TTf4\nvm4A+NYnc0VkL9RT7kB063RXNhd1dYIugBoc1ynLIuANEfl+zQZ8iDZ1vIY+JzakyFmUtB4n5hyO\nzmNcAsec44Scw7Hj4M9gfgw4GajyjHcL8AcbsTVNHD/ZP3YiEOvXo9+6UFqIkpSSDVWxqtTVdnVR\niNDgKqoYwhCWkpCYW4M2MGxARdjjNmKb9KsznpmMYQTwvo3Y34vIn9BdhYtR8VaLmhqH/PUq/Mf4\nKfCxiDQX1Do/nqaaHBYn8oAcm+PEnMPReZS0cP+TNmKf75RIHA5HZ3EdKs5Au00jwA+NZ061EbvE\nz9rtBByCDpwfX//kgsICKtIrWGaWra21tTlVVA2ZwhSyyWYe8xKN4RAbsQ2bDRrFeOZY4DzUruQT\n45nbMDxnI/YqEbkT+AXaFTsOrfurRjtXn0N3HlZC0wrTRuxhxjPTUK+7xliS0CNybIaxLpvpcHQK\nxjNTUZ+nxngc+Imbwepw7FgYz/wMrSc7qsFdhehW4z7A4G62G7uzOxVUMJe5RE204VKbsBAgQNwk\n1PD5kI3Yc1oZ802oCK1jAdpsMcdGbExEdooR2/NLvpw0gQlvofYptwJVaJfuu6h/3aMisqDB2gHg\nVeDQJi7v2YiV1sTrcJk5h6Mzaerd6gvA2U7IORw7HjZiHzCeWYlmrerP4e0OnFb3zc7sTBZZ5JLL\nSv9fkxiI06KQq0RnpE5vQ9g3o+Ktzlx4NJp9KzGeWYBhCZpN/PrpyNOv+AbIa9Fu1xiaZSwBzgau\nbrD2WTQt5MBl5tpEYGsH4HB0Ib5ky3qQucDpzlvM4dgxMZ6ZBDzN5kJuCzaykSBBokQpa9zNozV8\nDuxiI/aBtrxJZFJwbQAAIABJREFUtBFbjtbHNaRbmk2bPMaOOXWUHTUiw2Y8LSLd0bGDacA/gD+g\nQi6bxuvfpIXLu5q5NuAycw5HJ2EjNm488y76jhbgv8Cv/CdOh8OxY/JzdL5qsyxiERvYQC21lJt2\nPSW8BJxpI3aL2a2twUbs88YzDwA/q3/7RCYyiUnkkpseInQB2qV7CtrZWiAifxQRQSc/fFP/XOOZ\n36Lbr83hxFwbcGLO4ehcvvM/vwCc4VrwHY5tBxHpic5AXSIiyZpA0NBHrXEMFFGUjOttbK+Qq8dv\ngR+hUycscOHu7D6qBz1+FiAQDFO5R6B3be+vM4b2yd5QVdS9rKISQES2MMI2njmQzevwGiOKMwtu\nE26b1eHoXN5Ga1luckLO4dh2EJG+qH3Ho8CfRaTFbFqCvJmkdRJlbHsXMJ4ZZzxzAfA7/OkPw+yw\nRyI2sqY3vV8KEFgXIF47JeWT8OKeA0Zmh0vtt0MHlBanZ/61ifVygYdpeXbssvqed47EcZk5h6Nz\nWQYcbSP2kxaPdDgcnUlfYGe01utA4AIRGQM8LSKvt2PdpKTbWsFuxjMDbMS2KcNlPHMJcGf924bY\nId+cyZl7AlPRzNlnaVTZAfGCCRnxyh6loYyU9EDV7Nt/c2Wj3nnAX9nUTNEcy9oSs8Nl5hyOTsVG\n7BIbsW9t7TgcDscWzAe+QLsxVwCXY+3pRKNP/+Gn066+7bSpzTYwNMPopEWYOANbPqRJXqdBrdsE\nJrxrMGFUM6QDhTWELxsUW3PFlUsfen3q+nfvy4mWXdTYYsYzacBxCV7b1cu1EZeZczgcDkeXR0Sq\nReRC1Aw3BDxFPJ5i4rGgDYWmomLvuXrH/wA1vv0UuMofKt8YM4Azgf4d+gCUMuBCG7Eft3UBG7Hz\njWfOQr3iwgDzmDdjKENHpZASzCb7DeDf18nvlsHvlvWH545HjfSaYBo6LSIRGp3n6mgZZxrscDgc\nDkcDROQEamtuClRVZKWtW/lpoLryrrIxexQAGcBnwDwgD20MOBN4B/WOW9WwecJ45jLg9g4OeTZq\nc/RtMhbzpzSci3apjgZ6A9/ZiB3eynUuBu5O4NB1wNDmxow5msZtszocDofD0QAReSalrHhixqrF\nJwWrK39XtvPuG4DfoEa8P0RFXABtEAgCN6INA6c2stzBHRhqrX/dKckScj6Pos0be6FCDiDVeOZU\n45lerVhnfMuHANBUvZ0jAVxmzuFwOByOFhCRfYGL0Jq6N1ET4Gv97z9Chd1yICoiV9adZzzTHSgA\nUjootEKgZ0d1xxvP7I5Of6hflnWojdj/JXBuDvAtkIj42wjk2YhtZo6ZoylcZs7hcDgcjpaZDTyP\n1nU9h3Z1bkS7YI8CdkFrzB5vcN4JdJyQA0s22pTQUYwG1tf7vgoVr83iz2D9E4kJOYAnnZBrOy4z\n53A4HA5HAvgzSMcAFejIqrqB8jHgMxE5oP7xxjPdUG/J3ToinlF2FGMZWzme8RcbzENJNDr+HuOZ\nF4Gj6920BhhpI7bZmWPGM8cDz7TiUnvZiJ3VhhAduMycw+FwOBwtMlv2G7UPn8zsS8GMELU3o3Vk\nl6NbkDOBX9QdazxjjGf2RrN4HSLkjDWMYQw11Kw2mAOAHh1xHeAYNs/E9UVHeLXELq24xvuAG2vY\nDpw1icPhcDgcjfCHi38+Ih6tnRmMRnsaM6x257ziotRQTXom5aOKye0pIq8Cr9Yd/yf5dXo25bUY\nLHAi+hr7FjAL3ZbdCx2PFWxvbBbLSlayL/t+i9aldYg5sY1YazyzANi73s3djGfOQGv17mri1OWt\nuMyuuORSu3BizuHoQIxnsoD9gMOAkeh2zM3t8YFyOBwdzx8u+pmpDadOD1dX9rSBgCEWTakpqw7m\n5JZUVZD2ATC3/vEPy9lHnsgnd/ekMPtM2+fWv3BWpIwsEZH6Vht3G8/MosGEhTZhYI6dw2pWv3Q+\n59/XjM9dMngEOLve97eiViy/bDQ0z4TQDttE+AKYgG5f57c9xK6NE3MORwdhPNMbWMqWxckDgT07\nPyKHw9EaAoFgZjwUJlBbbW0gYEvJvjKP2Nfr6P2hiGxWcN6DwpP7sKF3LcEYcG4K0XFArYjcJiIL\n6x3aqrqwVJtKN7oRJEgBBViz6bLWWFaycrVEpLY9j7MlbMT+z3jmdfRNKehW6wM2YpuyE5kIDG5m\nyXlo80iYTTqkIBmxdlWcmHM4Oo4babzLrCM7zxwORxJIXb8qUNutx6016ZnHYuM9g7XVN5x/xxMf\nghaRNaSW8AuVpB6TQVVKORnryskIoZn4PYCF4DdQGL4APgT2QQ15Aa2Bs9h6t8BgO3jRWZzVL0gw\n3WJtIYWF0+30WaWmtBwYDjzpf+Cvb1AfvAnAXSLyqX97GpAFbGgoQgGMZw71z0sH7gO+RK1XUoFP\nUE+9R3JszmEWS4kp+YmN2DnN/PgKUJ+6g1Fj5YYUAvWbRcr92xxtxHWzOhwdgPHMcHS+oWnikKNs\nxL7SiSE5HI4Eue20qQb4NzAZrUc77orHXqxu6bwFslv/oawY+CxHFC5gxMWoJcmf0PqxC9HasP+I\nyBu+8W7fFJuSdzRHvzaSkYG1rOU//IdaU7sB+M019pohYcK/RevJLGAD1Cybwqzn9uWLW27hwhBw\nLJrt+xy4BzgdzXp9IyKHikgucAOwE/CEiPzH77J9Fs2gvYmOGlvrH7MOqAQK+tl+/brTfUIJJSl7\ns3f2MIZlWGxZBhknichrLf08jGeWsmWGrtp/LGn+96XATjZiN7S0nqNpnJhzODoA45m7gYubOeQq\nG7G3dlY8DocjMXwh92PgDmAR6pN25BWPvdiq6QoiEvI/R0VkKOChth4ZIvLLesftXUvtewECAYOJ\nfcqnL71oXvy5jdgCEZlMPP4eNp5CLAYh367OxOhv1lason8pmD7+Uh+g4iwdiAIvA6ehHbc/B3LR\nbFsFMK+MslOWsnRgCikjn+GZyVWm6nBgXJ35sC8Cn0XLQrDYnhabZjC1BnOviFzT3OM3nukHLMGf\n71qPOWzZDTvJRuxcHG3GbbM6HEnGeOZw4LwWDkt08LTD4ehcDkaFVwpqr/EUKupaRYOGhAI0OzcQ\neK3eMSaNsrsM6UGLAQJVk5j0xAuRFwr8+2fdcuaJL9Vm5RwdT8sKxrNzDQFjsEFbYdIzIZ4BAeNv\nAOyHbutGUdH4C3Qr9xKgH3qQRUXdlCyyvh7LWGuxGVdyZdRY87XBXC8if/KbNo701zRAjcF8ZzBD\ngcKlsdxXhl49Yzfg6yU3H92UpUg12mFbJzYXo5m/hhnOarTT19EOnJhzOJKI73r+D1qui2tq+9WR\nAH633M3ABuBW5xzvSCKZ6LbmeuCLKx578Rz4vh4tCyhvrTmviFSKyI1ADnCmiCwFZl3O/U98w057\npFBr3mcPO6v7+I/X5PZ+ve68206bupPNyNrdpmaqEIvFLCYUMMSpJM3mssEW0Qswdc8nFhVy54lI\ngYiMZ/MJDKbe5yz9wmAwQbTb/lQ0w/c/1EKlzi4kVh4qf2Rmn5mDigLRqrLFl09D7VUWAn9o7DHb\niN1oPDMEnYhxDLDaP6dhDV0NurXraAfO18XhSBK+kLsLGJDA4Ss6OJwdnSOBK9AXkueNZ841npls\nPHOP8cwhAK0cBu5wcNtpU9PQura1qGXGr+F7IXcuWpP2S38SRKsQbr/tem5fvl/8w9sCtZWDqa05\nscKmXTWIVVSRxsDwar7uN3BY/oDhx9eL5TcmWts3pXh9MFyyMRAqWpdPPFpCIFrYk8Li4ayqrN9D\ngY7aOlRE3vRvewtY1iCUxmqrLJrRW88mv7ph9e6f88qgVz4sTi3ulhFL6Tc68M3kKebznCC1g4de\nPaPJN6Y2YquAC1AbkyiaQMpl8+xcNltuxTpaicvMORzJ42J0EHdLvA883MGx7OicU+/ro/yPOs4z\nnlkF9DSeiQD32YjtUOsGxw7DYGAE2PcsmF8/NuM7//YUtPty2YqMFUfM6T1n2FPTn3oTeD5/Wn6z\nheciYnpQ1OMizIXGWrMzSygwvfjWDjHza4fOnxz+amJmsDzwXt6hNmDpt+uKb34i8sKr2Sp+Bgdq\nqq0NxgFsIBgcRygctNj4avrOKKTHmWBWoIII4AsRWVTv2jERORj4FOjJ5jsCBoijwvUttOFjMTBf\nRFKBbmgjBMDt6DZxpVe4cL/JwS9HpgbZpcymf9XXlAHFTT5+G7GrjGf+i/7NLkW3fqvQUWgHAIt8\n0edoBy4z53AkAeOZ0SRmkrkAON5tC7YdP+PWmDtEHWloViEHLWKfZTxzgfHMyM6Iz7Fds6J7Dj16\nDcv9Zd+dsqc9ddkReyI5YaAWeDNOfPDXuV/nRk00CpyACqQtEBEjIj3lhhuGm6qKPxTGMv++iCEm\nbgL0YQPZ8aKYqa6seL964u/X0nOfz2NjPqgoyS4buq6gfOLyb4cAF5UOH18SS037OJaeVQzxWhsM\n1Nb26ufXvRkswWcrSS8DfoWqqWJgfiOxrAB+i4qxOuFp0fq6p9E3QmeJyAwR+cq3LumD2oVUo00M\nL+ZPy/8OuGZIbTSQTiwAMXJM2Qg21cQ1R3d0+kWdaEsD9ge+AoqMZwYlsIajGZyYczjaifFMT3Q2\nY3ZLxwL/di347WYouh2UKBOBvwDzjGeuNZ7JSEYQxjNj3VbujsUVj71YkdEjbZANmAobCHQbE142\nY1l5zpyJy195Jmv+7ECsuuiiwnDhcxh6ohmt0iaWOhq4Gxt/xQYCFxCt3fuj2gnLSsksCxJdHo8G\n7gtEaw++/rY7Fuwk8z/5mlE/6F1cOmPE+lVV4Vi0B/AjwqkPVgwbN6Bq8Kj/VQwb91jlsHFv29T0\n9aiwfBZ4CO1SPRkVZqU0IS7ROt4foZm3SjRTdxdaN3cjMK6Rc+ai26NP1DVz5E/LX/9Vavi+SmOi\nAbDlxiymBX843zz9TP/bff0YQDODu6CdrbnNreFoGSfmHI52YDwzAvVpSvTJKKUDw+kS2IidjXYL\nt7YDLgz8HvjceOavxjP92xqD8cwpqMXCz9q6hmPbJBSrftHaQDjHlpBFZVVRTdqAvLSyQwzc2+O7\n757YeVnWPcD/ATflT8tvyntuClAGZBOLVVgTDBfHMvIzqJoXCvDd8Rnv3XfdHfd+UnewiNQCNwFv\nZFC+oQcbUrtRPADoQyCwkVBKBcb+dwSLZ+3D7JsvYvrpqBDbB62/jaPecmsbC8a3R5mJiqdBwI8t\nnBuHI2JwdEUgdLuIZNY7fjma1X4ErRP8Hi+v912X9u2976PZWSdVBoOTkeKmpkDU0RcY6389CxjS\nyDGNGQs7WoHzmXM42oHxzAzghwkeXgscbCP2gw4MqctgPLMbrRPSjTEbEBuxM1px3eHAx2gWZA1a\nk3dTO2JwbEPcdtrU403Q3B6mJvugPt+VpgZi6XM39u8eCsQZkF4cWF+d/sLC0rwHwFQAH1zx2Iux\nhmuIyEHAg8RiKYGyonnhovUzLxrw+qLsUO2lqEHvN8C5SPHS+ud9I7sOKybz9RpS+uSxvuglDrl0\nAz2GAS8Lt6ejUxoM8Hgcdi6g10lvMGXtIoZVoR2hf6ub+tAcIvLjODxsIGDBlqSkFuXWVg8WkbJN\nB+UYIA0prmx6pabx3ywdg4q3a1DBucZ//A250UZspC3XcShOzDkcbcR4Jht9Ak3UM+7vNmLP78CQ\nuhzGM2OAP6PdrW2lCngJHR7+cZ1pahPXC6ICcGK9m4uBi2zE/rsdMTi2EW47bep9wCFAMMXEnhqb\nW3DfvKK8Fw/s892Yr4r7xKtjoWhhbdrCnJTqNdaaW1eM3H8mcBbQA5guIqtF5N+ozQfAeyLyAyRn\nHFqj1h3dEp0BXIIUb/p9k5w84FULaUbNfX+EFH/t37cf6h0XAA4E+lqwFjbMYcKUGRzynYjE+r71\nWQDNvhVe8M6zpUDIz/xtuoxIn7g2I6QCrMvo9t5frrr8wHpxpKwJBq/+KD3tsKx4fP6hFZU3IsXN\nZsKNZ/ZGs5FHoCUn5/px1DETzSQ2xk9txD7Y3PqO5nHdrA5H2zmfxIVcHPhbB8bSJbERO9945jh0\nDuQJbVwmDTgRfREqMJ75s43Ye+vuNJ4x6P/zcLRbeWKD83OA64xnKoEXXOfsds9/0W3S2lobfPSQ\n++cuTbtw/L7VseC7AWNHWBurODTv6wlDs4p3NcQPe4F+J3zNiAPRZoHjgPstNs0ELDZuMJi654iv\ngAfQrfl1aIPB5khxAZJzrVFx+C6bmxXPQj3jDkR/5wBMHNPtE3a9GZgpIsV7DN55av7A4bV9i9bX\nxGHPAKSIyDUi8t/vLyOyVkQmV2PurUxNXfXx8HE/aRBJ3r+7ZR+zNCU0PMXaXfNisfBj9+z0y+ey\ns3qgXa5noGPOpudPy4/6dahvoj5yTdmMNPZ3sQTdLt65iXMcCeIycw5HG/C7V99C60ES4Z82Ys/t\nwJC6NL7g+oQtxwS1BYvO0/w7mrW7D+28S6TB5VfAP2zEliQhDsdW4rbTpoYBc8VjL1YjOSOAy2MW\nXl01an0qlbsc1G/5icZgsNhXzP6LZ8UmFkN8BaHwXzKHFL6yIpz3n7XBHscNKFlXmrm6di8vcuMS\noG7rcgzqRfkZUtxqs9xCGbT/m+z52iTmhfuyPjaTScXvsG8mmACQ8vHQMaYqJVw+cs3yjX1LN/YI\nqMXJPBHZP+GLSE74+l49nis3gX1rDBVnF5e8fX6/vPUxYw5C39i8hb4J+r/8afkLAIxnHkFFXmNY\ntPFhGCp6P0WbLrL8+39oI/bl1v4sHJtwmTmHoxUYz3RH3x3/jcSFHOg4H0cHYSPWGs/8EHgdmNDO\n5Qxwpf8RQ7MNiXI78CvjmenAH23ElrV0gmPb44rHXqxf1L8PkBI0hEf1D8xfVXtquuE2NWkzUFgZ\nzgxEy4aEitdPiGdmr4kPTZu7Oq33nr1rNs4vyskeftW6O89G7lyMbps+iRR/hWbp2sTTHHFMTzaG\nP2O8+YqRwRrSctCt1wBghq9baRf0HZJeFQotBPZAf3/fadVFpLhm9oOjzxpcGz1nn8qqzOWh0Isx\nY+5BhWEf1I9vEf7kBuOZA2layIF2xk5Cdyg+QrOLoNMmrkdrUB3twIk5h6MF/DqpKcBodIRU9zYs\n06YiYkfi2Ihd609/WAokxX6E1gm5OgajL1DHG8/8DXjTRuyXSYrH0fl8ApwZw0yC2mPWBsuzvo5P\njo4IzAssJ6toiR2UFojVBIPVldjM7PMrl3Z7pM+oDXMqgumHjiv7Zm2v2o1Ho7NRa4BsJGcR2jzz\nOlLclLVJk4xkca9cSgxYKkkxCxkdQjNfcSDQq7yE/Rblv43WkR6MviFpnZgDXj5/wXq0jpTx08cb\n4A3UBmUO2s37Zf60/I3+4fNQYde7ieXSUbP0bmwScm8Cp9iI3djEOY5W4LZZHY5G8Gd/7ou+KO9F\nYltszbGvjdiZ7Q7M0SLGMz9C6562FQrQF633tnYgjjYgOQHguxoCPSttemap7cPS+B7szuIvngoN\nmry4uJukFK27GhMwVf2HWELhp1bsknva1YsfnDascsWBAew4NJtvUX+4Om/Cd5DiVhf9F0r/y4rI\nuS1KMFBIln2JI2tRM/LXUeG2BHhARGJIzmh0K3POZo0WbcAXdAOAinoi7nuMZ9IAD7iqiSUeRL3u\nstB6u91txLZazDoax2XmHI4GGM/sDPwLmJykJR9xQq7zsBH7qPHMVJrf9ulM8oD/Gs/cA9zhRhdt\nl9gw8bAxlTbEqkBe8BlSTHTCmczelduLrxWRw4Hd0G3Ilx889bI4EnkIeBWtMauz5hiHlgHMQYVX\nq/mOIUt6UUgW5aRRxVRejX/EHu+up+dNIrJprpbkHIuO6EpDmykO2Wwhrd/rDRQjxU355X3PfhUV\nPykKBK8IxuPrxj80bk+MKQfORme/LrQRW2U805SB8BeowfF7aFbyNSfkkosTcw5HPYxnjgIeZ1Nh\nbnupRGuvHK3EtzoYZCP2iTacfhkwnvbXzyWLAejWVBRtrnBsP/QH8kuNqY3ZeFY3U903sGnG6e7o\nNuyewOFAkYho/Zdmwlb5x/0Myfkt+gbDoFNMHm91JJLTezyBe95ibzOWb2wPSuhOaWwPvpqDFDcc\nkHopkOlf7wAkpz9SvMoXcaCzUk8HFiE5lyPFFU1ddvz08SmDQik3VhiTXRROGYe1YG02gcAT6Jiw\nOeOnj78S7QpvSDlwpo3YOPom2dEBODHncPj49VYv0LY6qaZ4yUbsmiSu1yUwnhmAPvH3M55ZbyP2\nrdacbyN2vfHMJcDbHRFfO7jBeOYbG7HPbe1AHInxbFamqTSE38jICAFrTi4p5ajKqjx02sLzSM6+\nAguQ4ldbWKoQ3WpNRZun/utv4f4aKV7QYiCSY2rh6RDx/tWkmhhBKkgjm4oaNo3Iqs8y/7NFbUEK\nkZyhwOVol/apqMXJWLSha07dif6W6vHo7sSzqC3KRmvoHtDJsCZujI1bm4ExQ1EtcSDqK1eL2jYt\nQYXwlzZi81t8fI524cScw8H3buVPklwhtww1+XS0nndQXzeA241n9rIR2+JWUAO+S3JMySAbmG48\nc62N2Pu2djCOlrm+d8+jMmIxGzUmbGD+J+lpHx919rxfIDlpwC1A93LSSm6TGxbFCawBnmxo0gvw\nfK8D/7p34Wcn94iV7BPAxgI64L4StcCZkkAowTimVwDLJL5gMYOtIR4bxIrfDGbDu6BG5vW2Lx9F\nZ8SG0W7RIcDeaDNCX//2GDpisKFFSh5wLJrVuwmYFsAe2zeedfcR5euP/ig9JZgXjdlP0tMqY8Fg\nCjqFZQlwLfCFjdg5ODoVN5vV0eUxnkkBriO5w54/QEd3tdpHqqvjN58MrXfTrqgpb6IGzXWsAK6m\niXmVW5EcIGI8k6ytfEfH0r0iGAxb2Lh7VfXEPxes74bk9EPFUDZQupHc3Qx2AmpcfbmI9Gi4yCu9\n9j8kGgjtDiZs9Xcghr4GJ9bpLsVRS/D6UtLLw9TYMlLN7fQKDWHxvcaULDCeeRq4yvdcBK2RK0EF\n2a7AY2jNnkGzhE/XEFpcRtojSPGyBlcrRq1U9gNGAn9ZGg7n5uedvfKHVem1T6xey+3rNtirNhQG\ngtaWonYjX9iI/SfqIefoZJyYczi0tiQZGbRSYDqaUTrIRuy2mBnaHhiCbg3V5zpgd1/oJYSNWGsj\n9hbgUPT/ZluiD+pJt81iPNPLeOY3xjNTjWdGd1Xx2S0W65sTjfXpF42Frt5Y+OmhlZUxYCJSXALc\nD3wzh/FPxwimonYg1wEfichmv6t7Fs8bHCQeWJPSvaSaQDmwEX0NTlj8pJuNzw6kZMbhpJhfsICn\neAYMKcAoVEheBzzq+2GWoTVzKaid0gi0Ru5+4Nc38cvZt3N+9z9xwWEisleDS9UGsGv6hGJ5Q1Ni\nvXODscnA03usuP3n/atXpwUAC4EDKitNTjy+CDUPrgLwa+McnYzbZnV0afxsz6XtXMai80FvthG7\nvv1RdS2MZwJoAflU/6PhuKw63gcuMZ65r7n5qQ2xEZtvPPMRcFi7g00u5xrP3LUN1xMdhPoqfo/x\nTBma7fkUtcJ4xUbsws4PrZOQHHNYz+6HVhszJgAmbG0J8A0wX+8vngXM+kyF2wWoD1sNuo3Zk3pm\n4QOrCx4uCWUe36OmeOdU4iVoc04QuAzJuR8pXkQz+G9kppebytM+Y0lzh54KHDCVioI/E84aRjAc\n8KdDGFhnoBIpLo2JHFpJqAbddt2LzY17+/VNsRP2zoiWrKgNdJsYsmlzK+n94+61QSqDVMQtwWic\nYLUNFgcC1+dPy/8o4Z+po0NwYs7R1dkHGNjGc8uBZ9BRXW8mL6QdH+OZbFRcTUXrevokcFoAuAc4\n0Hjm/FaOzPox8E//etsKAeAm45kTt4VshvFML9QjrD9aQ7VvI4dl+R/90f83jGdeAG5EpxpEbcTW\nNHLe9ofk7ALc+svC4hGz01IDA6NRBkZjI1CPtL1gk6ISkaiIlKNb+/2AD0Vks6kvh13ySjV1v3+S\ncx46p7XuTckgNp/Duhl1Qg79PU6Evh8S7buQEMMJ2TgYA7YQqnpKcZ2B9d/Rju9C4MUG568rjplF\nmUF2mUg4p7CoF2OyVwUX2RRi/TPZuaiK5Vkh1hWSEjMmf/z08ZOA+fnT8pvsiHV0LG6b1dFl8YdD\n39HG0+PAj2zEnuWEXJv4L/AUao+QiJCrzynA2cYzuyR6gp8xPQutZdyWOA641nimMeHU2byJ2uic\ngVq7JOqzeAxqz1GOdj7uKFwRt4zOjcbDh5VXMramFtRaZgONZ4/fR33l/gI0HFy/OVL8d/S5Zx36\nhrClCQ1/JnEhB0ChgYupplxr5GwVMD81/H0WVUTeQr3x9hORzUpC8qflV5XHzQ1frM87Y/HiXdeu\nLBi+uKwkM2aCAbssLcV+1DODJempNh6zMdRY/VLgwtbE50gubgKEo8tiPDMC3TJpC3faiL0smfF0\nJYxn/k0rX5waIQrcANyd6AxU45mBwPPoi9i2RBS1l9jTRmxDv7BOwXhmI20bVVefVTZiByQjnq1N\nzfXdIwZ7DRAuqkmN9k6vqkGF10bgn0jxZw3P8evkrIi0yRC4MYxnfgb8ta3n97QB7kzLXRpPSc2v\nCATP/vmvlm9ozfk/+dNPfhWOh086Pv7W4I/Sew7MrUk3E1IK7PpYKqGKzK/+NLA4vzIQKASq86fl\n/6qtcTrahxNzji6L8cwBtGFmIfAwcJ6N2C3sBxyJ4Wei3kaLs9vLP4GLbMQm1BVoPNMNdeS/DHXH\n31b4DBVz0a1xceOZYnR2ZnuIAT1auQW+TTLr4jH77pS58emAiceq4qlpAzJK/wDcgRQnTaglgj85\n5KJ2LLEBmGgjdkV74qiW7lc+wBm3FNHNZFJpR/Id2ZTWfNr92zv+kZtTCDybPy1/x62f3MZxYs7R\nZTGeORUVfkbbAAAgAElEQVRt10+UajSb9ExrCvAdjWM8cy/J25q5DPh7ohk6//ojUZPonZMUQ3v5\niY3YhzvzgsYzQWA0+jN4KknLHrIjlB6svbp/VlqwdnYA2xv4Iiul9nCkuNPfwBnPDEMNfdtqnfQ1\nMLa5Nwki0h2dYFEAvCMiWzy/eXLDOAtzUqgJD2al3Z/Z9KDIdqPiY6R43/HTx6fUhgaFFpzxUmJW\nK46k4hogHF2ZH7Ti2HLgbBuxT3dUMF2Q54DzUEf89nIHcL7xzLE2Yhtzw98CG7HfGM/sh2677pOE\nGNrD9M4Wcj4/Ah5J8pq7ovV32zV90sqjaPY4jE5MSAgROQFtbigEJotIUTtDuYr2eWCOAv7PN6pu\nSoyeiXaUg/oyftXwAEvgohyKA9mU2b2ZwyBW1TmsDx763M07x3peOtsGMtMHvPzYSyuPOu3YdsTr\naANOzDm6Mls8YTVBFPixjdjnOzKYroaN2NeMZ2aiFhjJYBzaHXp9KwTdeuOZH6Bb5ycnKY7WUkr7\n7XESwjeUDaFdp5aOeQ3o3wFrdj5SXIXk3Erd/NXEs3LTUTPhnmhDREMPt4QxnklHG37ay6+B7sYz\nlzWRva5GGyJj6DguRKQXWkPZA7ViGdON0qDFmBpSbBxsUJ8b342F8i6xgYwMbDQGwSOSEK+jlTgx\n5+jKJFpD8rQTch3GqcDnqJ1DMjgDONZ45lwbsU8mcoKN2CrjmTOB9ahXWGdzXEc1PRjPjEfnZE5A\nnfz7oHWK3xrPvEPHCK+xHbBmpyMiBn6VDnwqIktacWoKmyxHBrczjLqxW8ngPFSU3dbIff9Gx9+t\nB74VkQOBn6PWJRszKdu1hmB2Id0YyBq7iJ3oy8ZlPSn5ErgGExoK8Z9aEwraQHrLc2YdScdZkzi6\nMi8DMxM4rs2dZI7m8ced3ZnkZbMBMZ65zHgmoRdCf+7rhehW0xtJjqc5rka38jqKbsAlaPZzAJsa\nTkagL+5HdcA1D0r0576N81O0e/UZEdmvFefdima4YqiXW3s4AvX1SxZiPJO5xY0i5SLyhoh85tfL\nTUYzdOnA2P6syQxTa8rINAsYbuey6//u5rzhSPFUpHjp8h+e9U4s1HeXeErej+PhQeOTGK8jQZyY\nc3RZ/O7HHwDNvZOcuSMUc2/jPEBioro1jEXHZU1L9AR//Nds1Nj1ONQ7rSO5xkbsLR3cTNNeq5G2\nkE77ui+3FQ5CtxEzaHoqyRaIyA3om4IDUA+29vAy8ATAiTbIX2wq+9tge9bLIjFbnhnobNYPgcXr\nyLYT+Ip+rKnsQdEDYI4Qkc2MrlcfdvC3qw896LE1B0/c6gbYXRHXzero8vg1Uy/T+HbGVBuxMzo5\npC6H8cw4oCPGWlUBP7UR2+oif+OZXOA1NhWGJ5MbbMTe1AHrbobxzLm0PzvUFkpRO4ztbj6xiOQC\nTwPDUEGzEjhHRNpl7dFWjGcCp9nQM/eSdmwMWE2cfamgwvgHWDieEOMJ8CRR5ptmtVQpsJON2Oa9\n5iQnOw57WQKre2IvHsSgC4KUso5Vc1eZ2sk2YjvVnsXRMi4z5+jy+Jm3HwBr6t1cgs6lfHmrBNX1\n+BIt0k42acA/jWeOb+2JNmKLULuG2UmO6XedIeR89u6k6zQkG7jPtz7ZrghSeyPE90YL/2uAH24t\nIQc6uP4R0ueGIZaBDnPdhwAX2BR6W/g9Ye4hlYMIcn7Lto3ZJGDWXRTKuuC79EE3fJ3a555cSs+Z\nZ+bxuVnKKlO7Ftip4fF93/osMOyNmb36vvXZdvf/vaPgMnMOh4/xTA9gDJrNmW8j1s0Z7ET8Tstz\n0Pmr6UlefgWaZf28DXF1RzN0eyQhjlvQ7dVOeeI1nvkpuo29tbjVRuxVW/H6rWKp7PKDVzjg4QJ6\n9Y0TiEJghoic2OmBSI5Bu1ivASqrIcVgR4UgXol9MQ1zuIGMOBQGoLuBFAuVRdh7epqyP6MjvF5H\nO3EbUo122X4D5AFP1DV4adMH48dkzr9rUHT12EoTzfilWZcxv+pbgPU2Yns3XGzhHycE1gVzvu5X\nu2HIwvQhi5/ud8ToB0+9zG21djKum9Xh8LERu5Ftb3Znl8EXOP8wnqkF/pXk5QcCf0QLylsbV6Hx\nzOHoi+OkdsRwO50o5Hy2ePHtZK40nlluI/burRxHQqRRdXAqNcV5rKWQ3NVVZJy+lUI5Gf0bCNep\noo3G8GU4HN+vuuawIOQA8YA2uNQCGCjogbmlznrEH5nXmJhLBer7wJ1gPHOYjdiZ6O/3pV9U7TJo\nue2bVhYIpIX4HPgW9A3NlovFaiaOrF2+UxwTnVQ2f3jK6vh4uKzVb5oc7cNtszocji0wnjnfrxnb\nGjxCcry1GnK476bfamzEFgKHoU78beEe4IrOFHLGM31QW5Ktzc1+dnObJ48NL+zJ54uGsPrLIaw6\nT0Sqt1Io49EdVQOYFKC3hT2qawJRbWrZgDZnPINOMXkH/ZupRnJGfilZucDlCV4rBRjuf51THagO\nr0ldbtfbzFBNNDO+V3Q4YRsGaNTqp0dt0cKgjVWGbCxkMRW7lc53I722Ai4z53A4NsN4Zm/gPmAV\n8FJnX99GrDWeeQYVdWcmefnj0AxZq/EzdIeh1iWNZTwaku9/zANu3goj4H5KI/VNW4EMQOgkY+R2\nIcWzxkrOaWP5tgYpbv2MXMk5BDgNrbP8e2NzXEUkA93qTAF+iQqpB0RkroikAEbgUeB0/z7D/7N3\n5+FRVtcDx793JgtJgAEEREQEFQUlilVc667VWm1d21prcatrtXWr1Vbf87Z202qrtbbWrbjvWtef\nO25VURGNCoKICAjIOuzZ5v7+OG9MCFkmySxJOJ/nyUMy8y532ObMvfecA84BZWgEB7wK/BlJvtfo\n/ucAO21BbHmJZ9M1jnT8t0GC0Osf9Pvg6MpY5bJ+lX0HVtemUjXUFPSkJ0tYMr2pk3tfPn8Vkiiv\nJn5UIbUPI8m0u2WYzLE9c8aYr7nQDQAmocuSy4CjfOBfytNYYmiJhEMyeNlnfeA7VKE+mmVqLaB7\nCTgmWrrPuSggf5HM7z1sr0pg42wVR+4UJDEcuBUtvhsHrgFmIcmvX7OInAD8ES0qfAWwB9r2azna\nOeI5tLDzzcJf/4q2vBuR0kQe57XrwhfASCS5/qyhJG4A1q7GDxrByuO+dGm9v//JB/6Suh/Kx5cf\nCxwxbPmwTbZcumWPN1Nv7v4O76RqXW2RZbF2XrbMaowBvm66fhcayIH2gzwvX+PxgU+hs0uzM3jZ\nkVGiRbs1WHJ9r5lDHvWB3z9fgVzkPDpPIAe6T+uUfA8iYyThkMTWSGI0koghiRi6rBkD9gE2Q4sH\nX4kkhjQ481R0prInui9uCbr/7T3gcmBY9Py5wnl9gD2BTWOwVwxej8NrwFFNBnLqP0Dt+9ROnEfa\nEzWNSwI9Bvz7896fX3Stv/bOt9xb1Lra8RbIdW62zGqMqXMJGqQ09Fo+BlLHB35ONMt0H9CWKvzN\nGYruR/qgg+Na4kJ3IDpD17AI61J0rHkTBav75XMMzTgRna1qUTT+IqA6CuhzSzNJC5FkVQtHlQMX\noMHbeOAFYA26l20L9O/EKvQ9dnPqWwc+jbZWq0X/7lyPFqm+AZ2RA11W9cCFSPKE6LH/AXu1Pvbk\nRGDioeKGkv52gnWCuYpxFZXAy1Htx6uih1v9czP5ZcGcMQYXuoPRmYHGAhe6iT7wE3I8pK/5wH/p\nQrcP8AvgCNJ5U2vZLS50B/jAL+/guBoGdP2BO9BSHMs6OL6OiqNN3jubche6B9GM8RVozbNC9Peu\nN9pubOvo57oyQbnt8ymJOHAmsB+SeAJJ3tbEMcOBH6K/x4uBjZGkRxJ/AX6Dzsz1RmdGp6J7Juv8\nGXgCfe/9AP09OBd9zY76QA50u0P9bUWGAEcDs4DHGndgiMYW+4LBv3uZMUc8z+dc5ZPMb32pdUXj\nB1zoeqEJD6XAIz7wH653lulULJgzZgMW7Us7HfgbNFlxtBR42IXuT2hV/Bl52Mhft+R6jQvdX9El\nqkuir/bYGZjuQnca8IwPfLs3bEcB3e5AVT5+X5rRauXYPDo6+krHp9kcyDp0mbQA3VpwKrBZDW6v\nZ/9+2NSTR1/x5vz9xvjouDjwD7TkSwrdG/l0NJu3FPgc/f336D64exrtmfPAhyLSD214XwAsRGf1\nGvZMXYn+m2xoHLoM+w3gE2BK45exgpLfz2XgL3uyyo1m+9ROvB57kpZXR4s8RyOJCcB8JDk3mhn9\nN1ry5Efov3vTyVkwZ8yG7RzWf9NorC86o/AH4FoXuhS6Ufu1XBdWjjJda+h478+BwKPAfBe6pegb\n8c3AQ22dsfOBz1f5iuYcRPfYD52b1yCJUrT7yJbo34ne1cTdhz23Knux79jfA/8k6o8KjECX6gvR\nYO1faPB3OvrBZzY6W1eItgF7opm7notmVjs0yeFM9O/g1ei/t8uiwK+hfmi/2PlosLfuyxApPIeC\n7w5mgash7rZkTVrTmv+g+IJVpM5fAlwtRT+LwZCU47BBftCQeTKv+yasdDMWzBmzgXKh25n6PTHp\niFNfu+pC9A3u+5keVxo8mt2XCYOiL9DMwptd6P4BXFpXfLUrcaErAi7K9zgy4EUf+Jb2rGXMStfj\ntLWu4OI4vgDv9+nrVz++oqD025+XDO7xat+dp6At0eqCuWXo8uhOwAz038OF6GxxDRpwvY2WDrkT\nSX7VzG2XoYEcwAwRuSv6vqVSQH3QJeoyWHe6TUS2BR75L/sPOZLnqaHQe2rdIsrQmLMZHkbQc5OZ\nQH883yb+4DAqY4v90VPjbPWKiFwL3NZEYGk6GQvmjNkAudAl0I36HVmSm5Wh4aQtWtLsj75ZHpCF\nW8TQ2cqhLnTjumApjX7krx9rJsVc6GJZT4CQxMge8LsST4kDlhX06ksNX961yeFj/jD8tNO8c9ui\nNd+i45PzkcTWaP2+LdDevXXBVTz6tRbdC3cGkngUSTaVRHQDOrtWi+61RER6oB8s5opIdRPnvIlm\nt05FZ/+IzisC7gFGfMEwN4lt/Z5M8jFqU89S+8quGmjuTH3w+AnwVJkvG/stvjX2eQbEdmQ+S4oX\nxQakVteMqZ4XX8xHWz/JJjWrKKv70LbevjrTuVidOWM2MNGemPvR0ggdcZYP/D8zMKS0uNBtDkyk\nPusv2xaj5TQe60T74VrlQvcinTObta1G+sBnt5uAJHZJaQJLGeBWxEq/SKRWfw9Jvg8w6KXJ7uv9\ncnp8KZqZWoZ+EFoYPfMlOjO3GhiMJj84tObcYQ33zTU5DC0W/BtgKzQL9l/Aew1nxEQkjvZSXdyw\nM0W0/+4DNIGEItayNdP9wby6uheVc7dj5eiPXWozdIn2c2CCD3wqkOBHNdT8weFq+pIcsh9vFSVY\nyQI2SvVmNW+yE3MYPBktDzQCeEVE5rftN9jkis3MGbPhOYOOB3KgAWFOuNANAd4gd4EcaLbio0CF\nC939PvBX5PDeHTGJrh/MPZL1QE69HYMra+HHq1yP92qJn9Swg8E6gZyqBiagv7+F6ExuBXAyGowl\n0D11fdGZukpgb7TlVkt6VcXj21TFC3Ypqarc2MGOMbhARBLoDN47IrICDRobW4ruuzsDcFUUuals\n47ZmVvH2TL/vI6mtRoPKzxqe5HBfFVL4aa1zw3r1Xlnok3G3ijJmMzgWxy9bTN+FwHXoTLVDy7Fc\n1vAag16aPBJtIzYVeGj+fmNyX0rGAN1jk6wxJk0udN+lne2sGkmhMxC5MhLYJIf3a6gcuCTqddoV\ndJVxtmRfF7oRWb+LJD2SvCIuyZG9gwXH9bt8TsuZzZKsRhMevoW27FqN1pHbGvgTcC2a4ToNnWGL\nA8c3KhzclKVTBg1bEU+lBlTFCnwtbgg6O3cHcBtwcQvn/jwazwrAQ8zXUOCfZ8/7gKCF814Ezqvq\nEb90Xu+NnI9BNYUsIcGHbF2yhpJhaKJRXWDaVFrsiejS8GFopq3JE5uZM2YD4UL3bbTfaXEGLneQ\nD3zjyvHdWSm6zykTM5rZlqnkkHzqC4RoaYzORZJLgCVIoi9aT64YLSD8LyT5CJKYj/Zn3RUNsGrR\n5IU5X19CZBKwQ/T8QBGpGvTS5KfWFhaNHLFgzpa9Kld/Qaq2P/qhqRgYKiKumUSEXfuz2G3GvMLZ\nDEoton8cYsuX03cmkmx2e0BUp67iCvn14oHLF6WeGbxbbOCSpS6RWkYZq+KfrR3hIDUGUkMh/iK4\n69e9QGLPy4b84Mfv9dq217SyzV+ZVjY83/UVN2i2Z86YDUC0T+5poEN9SRs41Af+6Qxdq1nRuDdB\nq+wfmO37pWFfH/iX8z2IlrjQXYKWkenqrveBPyffg2iWJG5C+waXoR0gXkWS10W16Dy6h+0EtGXX\nTUiyFkBEhqOZsHUFgt8CjvzXPkcsjKVS5WNmT++5y+dTPkNn4w5C6+1dIiIfrXN7kYHA/TFqd/s2\nE4pipBzg/499XTWFNWiZlMNE5OMGY44/XlZ64tx48X6f+U0fLF1x0H9FxD8nBx+/Cx/ceN/gg3u8\n3Xu0n5/aOL7NrDn0rFwdBQgOiD2HzkruCLwp/PWfVa7gwOmlm7te1as+vbXquB8Cc0RkTaZ/q03r\nbGbOmA3DT8hcIAfwGxe6/8tBYsCPgduzfI+2OBvo1MEcWt7iWHRpujP1Z22LL2lb2Zx8uBBNntgG\nWAs8iCRGop1KkugS6aFohnEh8PfovMbvuyOBs+bvN+ZyYLLWBAZ0+bQlP6521bsv7DGvsHJNyvWk\nhiqKnMd5tAjxXDSh4utg7qOiwuMH1tT+Y6PaNYU1RfOPnVWwOAD+dJA8cxeSePGzkqFPL6fX8KTr\nXVoTK4hBXR9j59Cl3NfRTN1Paog9VORrDhi1aoZ/nANjwK+BWSLyWxGxPq45ZnvmjOnmXOgOo/XC\nwG21BzAmw9dsylvo3qPO4Evq35A7s7o6aEegs0JdjQcu8YH/It8DaZEkk0jyPiT5WyR5JZL8Etgf\nHf9g4Ch0P1k18N0GZ36Ktvjy0dfq6Ji2+nhWz1l8WTqPCUUbMYXh/nXG+hoKqtFWXBPQpCEdrsjZ\n/6066U/vV+1bkKqNuwKfKizxqV/MkW32jTpY7HbxZ7e4PRe8V7PVV7NXJ9asdJBqEJSlqKV2sMdX\nA6Ou4vTrgR+spOy8D9j2QzSzd2tgtIhYbJFjNjNnTDflQlcMnIdmoJVm4RaPudA94QN/ZhauDYAP\n/DQXurfRsgr5VAns3ukDDLRLRvTtsy50W6AzQ6ei+8+G5WtcbXC/D3xnmo1tizfRQHoZOkN6EFoX\n8cG6A0TEi8g3gN8D2wL/R8Nadq14+48D3eJ47NI9S/wmU4q2/s/elavG7cTyohLXv3aOH/ohcPw6\nS6t8XfrkzCp6zF/oh/aZEhtSuLByoO9TW9h7I5aeBSwAzunrV252xtL7Cu/lg/kf8s1UIYWJHlT7\nWgqJUeXXsCIGPfuWUPJsJT0qkeSzvYFakXnAkegewvOBJ8lhtruxYM6YbsOFrgRtQl+GFjU9C21R\nlC1DiGpbZYsL3aXkP5ADkK4QyDUWFT1OAr92ofszcDjwS2D7vA6sZV03CJDkJCRxHlCNJNcgicPQ\nD1Lr1GcTkRpazlBt1qJ47NwBtbW/ikH8Z6s+mbFZTc0rRZ5Uf79k4xHMv3GAfN44kOuF7jv9EOJ7\nVdOzalXlbosGs6r/9ryzuoTKjdEPK0tS+Nhqaoqm8s5W1/IuB3IggympHknP2mLeLnmEmXi2Do7g\niGtExCOJjYFigWeF8+ahS89r0OVdk0MWzBnTfYwGnsnxPQ93oXsAONcHfl4mL+xCF0dnFvNtLfBs\nvgfRUVHP2btc6B5CX89eLRz+OlqOYgy5zY5NobXaui5JLm/wfV0wnUllTrdIFfTwfothNbUpdPZv\n+gCW7ookHkCSiwFEpAS4HC2fMgLNrF28MxW9x/BxdU/W9gA+QJKfIYlfTSd182vU7vMAtVS5FBP8\nBEYwomgyy5nL58xzHnj/zcnB5NVIYhTwEJp5fA1aluUVYDO0u4zJIQvmjOk+FgGTyc1etoaOAYpc\n6I7ygc/kxudi9E0q307ygZ+U70Fkig/8Whe6Q4HHaLq48Dto6Zk1LnR7oG/U5WgLtV3RmZds1fx7\n1gf+tixdu1so8f7qFbHYTmWp1G4jK6uq0X/3KTR7dQ06y1YnAYwF9kH35wEsraSoKkZN5ZvFxQVz\nCuPbfytMDO0N/fZi1aQlsE9tlPaw2q3mfd5vPITbXeiGe3ofhs7O1wA/FZGrgJuz86pNa2yTojHd\nhA/8TODGPN3+u8D/udD1zdQFfeBX02h5Kg/eoeXm512SD/xKNDvx7iaevtgHfk103P984HfzgS/z\ngT8E7YoxFE2ueAzdyJ9Jw1zoemf4mt3KvhcvqNx3zdpjxlZWHd1LCwq/A1yE/lm+grb8qrMA2D36\nvq4367ICao98oFePFX/YqG+vv/ftM/ql0tI7VuEvOI7Cc+oCuRZsghamfon65KR3Ov7KTEdYnTlj\nuhEXuq2Ad9GNyPmwEm1v9DZwgQ98TUcu5kL3Opo5mw+vAWf6wGc6YOk0oiSZvwA/ix6qBPpFgXQ6\n538HeCKDQ7oNuMwHfm4Gr7lhkEQIbIHOzv0qKm5M1AasjPq6duc/NPyhuwpTqVtTMLaH99WnL15S\nnViV7Nsbyn5LZeGrrsW4YIoP/LbRPbeN7vl8wzZoJvdsZs6YbsQH/lN0WeUo4L08DKEnOhNwLvCI\nC11Ht3J81vohGbcA+JUP/F7dOZAD8IGvjArz/jJ66N10A7nIy+jvVzrupn4Zbg26fFvXf3URmhAw\n0QK5ditFg/FC1t1CdXyj4+YDp1fHYqtrY7HlI6qqP91i9cp+hxLvsz8FhS9Sxnd9i6FBfSKQJD9G\nkk9YIJd/FswZ0834wE/zgX8E3d/0ah6Hchjwz6iLQ3vNyNRg0rAQLeExxAf+zzm8b975wF8F/BAN\nBNpiFVonLR1f+MD/FLgJuM4H/gJ0efBL4GQf+Ct94P/Vxvubetehs8k3IMmvGjx+aaPjPkZn6NYC\nr521ZMnkGb62dxEOcMSAoyhkuHcc5QsY5tf752uBWydkCRDGdFM+8NUudAcCn5O/JvWnAgtc6C5r\nZ7eIjszMrUB70b6LbgTfD9g5+n452itzLRrE3Q48F+0l2yD5wN/nQvdkG08rQmdjW/M8cGX0/W+I\nAkAf+MejWoW236ejJDkb+A+AiPRD9zZOB7ajfr8caPD8L2BP4PPLqpLHHUaBW41O7dUCf6GSi+hB\nMXAABfzCr6W6/goDcvBqTBvZnjljujkXul7AreS3SfxvfeCDtp7kQvdN2j67eANwNTCrcXZtNEvo\nfOBTbR2LWV+0524VWsakJcf5wKddGLe7EREH9MhF39KoHMkf0GLRn6LdKE5DA7pHReSoumNd6IrQ\nosX77ehj7E+cJ6hhJp5r6E01Y6gmxu+ZSNJ9PQF7tQ/8hdl+HaZtbGbOmG7OB34FcKwL3UXorEg+\nkiMud6GbjZYxuL0NwVRrM3NVwGJ09u094EEf+A+aOziaAbJPsJnj0P1uG7dy3MIcjCV7dKP//sAb\nSPLdNp0qUgpMAQaJyIdAADwlIhn7QBF1ePgh+u/hFbSY92q05tsZwAVAZRM9U7cEdgN4z6V4j/oh\n3e0HsjP9WUQtQxhOko/qnmrLnkqTIzYzZ8wGJJpJuQltI7QjRBtlcqMaDbx2TbebggtdDM2QnYdu\n5F6DLuvNRff8zrQluvxyofsPMK6FQ+4Bju+yf06SKAD+gdZyKwJ+gSRXpH26yHHAeHQFsxhd/v83\ncHFHA7pn5PAe4J9aQL+9ZjEkXktRJXAL2oFhIHCtiIxvfJ4L3bFosd/jgb0bP1/myxjLWMYwhjhx\nXuEV3nZv1z1dA4z2gf+k8Xkmf2xmzpgNiA98JfATABe6Iej/AXdTX4sqmwrRWbHK1g6s4wOfcqEb\nBKzKcEFikzkno/vhdkdneXZHPyzUfUh4rMsGciqFdnEYhPZcrW7j+XX12HpTHxD+AF0C7VBdyFWU\nXL4JC/Z9n5GugFpqNVgcA8xEs4zXS1aIMsyvpYV9tN/gGwxlKGWUUUste7EXn/hPWO6Wg/6fcRVa\nW9J0EpbNaswGygd+jg/858DBaJPstm5+b4+NgCvacoIP/HIL5DovH/iUD/zHPvC3+MD/1Ad+NDrr\nc0D01bVbO0kyBfwZnU37Q1vLcIjIfLSV1i/Rsh4O6N2HpZckZfApSKLdyUlL6LORB2J4UsTqAuZb\ngEnAR8ALTZzWhyYCuVIP5/hCLvNFlFBNKlpyLaCAYorZm70bblD4pgvd2PaO22SeLbMaYwBwofsZ\n8Pcs3qISrYH3YRefqTEGABGJo3+nF4nIp2kcPwR4ZQBf9fkp9/YpoNbHdF/oWCS5rPkTEw7NSu0F\nvIskq6LrDerLsi+hlqX0AeKV6FaGkSLSZGa2C92maMmf4oaP7+njnEEhlcBE4jxDf8opZ1u2pZJK\nFrGIu7ir4aaMGmBUVNvS5JnNzBlj6izK4rUfBfb1ga+wQM50IwL8F3hBRHZJ4/iFwEtjmOLi1OJ0\n2XUoLZV3kcTu6Ozm7Wgiw5FfPyUyfyl9zl/KRvMhXo0u5/ZEg751uNAVudDdjLbeKm78/HxSeGAb\nYgykmjnM4i3eYiYzqaSSlawkQaLhKQWsX5DY5IkFc8aYupIdR7Z6YPtc5gN/pA/8m1m6vjHZJYk4\nkhiOJBoHXUcAvYqp3HQEn926SjbeUkQGiMjX+9FFJCYifaJfK4FnprLF5LUU1kSfaj5EE3qaum9f\n4FfoPsSRQDmsG1GJyN/QhvdXox/IrhWReU1c7efAKejev/XMcJ4KUiwgxTbE2IEYC91CJjKRJSyh\nllrGMKbxaR1q12cyxxIgjNnARRui/w18P8OX/gLtz/pghq9rTK6dDHwTWIgkAiRZ12D+TWDUKKbF\nhk76CvQAACAASURBVDF71AR2e6qQqknVFH0gIlehM29no8WqdxaRrcGv6MPKCRMZM6k/y+4qZ/pN\nSLK52eoqNPu1R3Qtt4xeM/8msjMwJ9qPR5QVeynrd3toqMkgrqHZpNiBGLXoFB/AIhaxmtUUUsiq\nrx/92nHA71u7rsk+m5kzZgPlQtfDhe44dLP0SRm89Bq0ltZIC+RMN1GO7kXrH33VuRuomcfGzGUg\nX9G/bxFVC4Ft0ESDnmggtxIYBRQMYHGf7fjkm9vwuRvJTFpMqNCg8ZfAvWjg+MZ9fOcE4GHgYRHp\n24bXsFFrBzxEDddTzZVU8UmUALHKreIVXuFN3uS9+nbPKWAa8FEH2/WZDLGZOWM2XPegy0SZdB/w\ny3TryBnTRdyNFuV9GW0DV8cDE5bQZ6ferFjcg8p7V1E2DHgdWBI9/xo6OxedEKOEygVFVFcup2eP\nViMsSX6JJC5AS44sm8cmFWiZn03R/sd3pPkaWs3CrXbwJusnji93y1nOcoBr0Kz3V4Fa66TSeVg2\nqzEbqKgg7zi01VdHvQ+c6wP/SgauZUyXELXOOgYoAe4XkWUiEm/YaSFq5XU2WtstBr52U+YvKWVt\n0SwGf1JF8TdFJK3addG1atGcUg/cKSI/SedcF7pvALcB26f9Aj0MZzgbsdFn05n+WNIlz7cEps7J\ngjljNnAudN8CDkc7QuzZxtMXA78GbrZacMY0LSph8iS6XFtMfUs9D/wHOENEWn0zjq5TifbC9cBP\nReSWtozFhW4lUNbCIfPQf9ejB/qB7MM+K4Yx7K1SSp8WkWvaci+TO7ZnzpgNnA/8sz7w5wB7AVug\n5Q+WtHJaLXAdMMIH/kYL5IxpXjRTdxRaymMe2t+0AF0uPZU0kwii6/wK3ZfqgRtFZL12XM2JZuMX\nt3LYbej/BX+JE//fNmzzYSmlWwAHi0ifdO9lcsuCOWMMoE3ofeBn+sBfg2bvNed5YAcf+J/7wC/N\n0fCM6VJExIlIYYOfV6P75x4D3kDLetTNxm3dhkvH0exWh76HN9XloTmHoHXtWnIC4HzgLzqN074Z\nJz4VeA/4ChjQhnuZHLJgzhizHh/4/6KV7U8DPo4eTqK16L7lA/9RvsZmTGcmIluLyEHA5cC/RWTf\nBs/VAL8DzgDORcuOzIm+T1eP6FcHuFpqnQvdOBe6v7vQbd7KuZ/TsClX0zYD3nOhOyRa+r0OLTP0\nCtrztUkisp2IHCsig9N6FSajLJvVGNMkH/h3gHdc6O5ASy0MBx63DdDGNE1ENgWuRwv81qIlRL4D\nTGhwzFpgFvCv6KutlqH154pSpHiSJ+v23QH0o+WuDGPQAsVDmnn+frR7xMNEM3giMhmYLCI9op8d\nOpM4EA0oJ6H7AM9DZw13Bi5ux+syHWDBnDGmRT7wa9Fs1ffzPRZjOrkSYBg6iz0AneW6M8P36A3c\nuZzl293N3TstcAsKGzz3Ixe6a33gJzZz7jw04GvKicBdPvDrdHUQkV7o8ux30FrCc4BzgL5oUHor\ncHN0uAOsXEke2DKrMcYY00Eisj+61/RdYDlam+5nwOMZvtX4L/hi1dM8veMC1gnk6lzVwrkTgL8C\nLzZ6/FXg7iYCuUI0W/1i4ADgYHRJeAA6GzccGCsiS4C/AI8Af2vzKzIdZjNzxhhjTAeISBnwE7Qw\nbyXa5mpea/XjROSHaJbr08D4qC1Xa1Y9wRM7LGRhMU33XtjbhW5oU4W7feC9C93DwFnAQ2iLso2B\n0Ae+qbGWogFbP3RZ9cPo+7qJoBRQICIFIjIVmJrG+E0WWDBnjDHGdMxaNNgZAXwJLEgjkBsMCJrV\nugnwFLCgmWOHoO3B9k6R+tsZnFEwk5nc2fwK7neAfzbz3PfQ8kOT0TZ+x6OZqk3dNyki2wKbo0uo\nW6JLtR5NxHgDmIEtreadBXPGGGNMx3hgEbqfrBRI0EyA1EAfdG9dHzSgWwpfFwYeBnwhItUishna\n67gn8D2HKwQYxjASPkHSJZu6dkv9Uv/lAz8PwIXuY3S/24ctHF+X6ACa4AAa0C1D23u9m+aMoski\n2zNnjDHGdEAUzNyHBjsvoYFdaz5B95c9BJwuIlWaKervLGPVc0VUPSIiBcBGQBE6+1UDeI8nRYpq\nmp38ay4BgrpALvq+0gf+g+Yy1KPkh4b78hag/WkXAW8Bz4pIk7OJJresnZcxxhiTAVGh4Ha/qYrI\nkBF8Nn000wrXUlQ1h012rWDUVOCHwKbAkiTJv1RT3esZnuFT92lTl6kCevnAV7V3HNFYCoH/ATtR\nn6W6GA3u1qK9aH/ekXuYzLFgzhhjjOkEROTg/Xnt0WKqC0pZXbMtn+4Sl6UVDY9xofsQ2K6Fy0wD\nRna0HqSIHAj8l/puE7VoQFcY/VyDZrJO7sh9TGbYMqsxxhjTOUyaweaf9GDtao97I05qRsMnXegK\naL3119bAtS50Le2bS8c30Fk+j/aSfY91u0cUAL/s4D1MhlgwZ4wxxnQCIrJwFpvt/hT777CEvgcg\nydWNDhnOunvYmnMOcJMLXaIDw9kbnZWrAn4jIrugrchAg7oUuu/PdAKWzWqMMcZ0EiKyBu2h2pRv\ntOFSpwDfdaG7DLilcUHgNAxFl1LjaJ9mgD+gS6yHoa3I7mvjNU2WWDBnjDHGdA3fbOPxA9CgayD1\ns2rpuge4BN0rN1BECqPaeVdEX6YTsWDO5JUL3YloP8AWC2waY4xpczBX52wXuit94CvrHhCRGHAE\nUA48ICIfNzrnKmAPtBaeQ+vhLWzn/U2WWTBn8ibaoHsscEcbjnc+8Fag0hizQYn+/+vXztM3Rsub\njG/w2GbAqWgNu43RFl9fE5EaEbkZ7RjxP7QsSbOiYsd7oXv6XhGRypaON5llCRAmn34EzPSBr03z\n+JHABBe68iyOyRhjOp2o1MhvOnCJ8xtluG4K7A7sAuza1Aki8l/gVBG5OY0uD7sDPwVOBA7qwDhN\nO1gwZ/KpArioDcf/EP3kd7MLXby1g40xppu5CziXZnq4tmJ74NAGP5egLcQWASuaO6kNrboc67f9\nMjliwZzJm6iNzJp0jnWh2wo4IfpxF+A3Uc0lY4zZIPjAp3zg/442vL+Etgd1v24wOzcB3eLyLpmp\nF/cGcCtwN/BMBq5n2sA6QJguwYXuNOBGtLr5PGAHdA/HH4Hx7Ui7N8aYLi36QHswurT5XXT/W2t+\n6QN/VTbGM2XkKIcmVMSAD0ZNnWL7m3PEZuZMV7E8+vUrYB9gFvrp9GZgkgvdbvkamDHG5IMPfI0P\n/JM+8McCmwBnA2+3ctqVLnQ/ydKQdkO3zlyAFh02OWLBnOkq6jKj6vZiLGvwXDlwVQernRtjTKdV\nPr68uHx8+Rnl48t/Xz6+fKvGz/vAL/GBv8EHfhe0yO8TLVzuVhe6A7MwzD7U753rk4Xrm2ZYMGe6\nih8Ak9CMKVj/P4r+1M/eGWNMt1E+vjwGbIvWfeuHlnRqlg/8Oz7wh9N8UBcHzsz0OIGX0f1yz0df\nJkdsz5zp9FzoegCz0fpFdbNv/0P/Y6vzug98ewtqGmNMp1Q+vnww8CugP97X9k6lSvukUk88eerU\n29K9hgvdt4CHgJ4NHl4CDGhct1NEBgPjgM2Bu0Tk1Q6/CJN1FsyZTs+FbjSaIdWwvtxENKu1Tg0w\nwgf+8xwOzRhjsqp8fPmPgKuB0gHVNZ9c99WiOaOqqojrSsRE4CYk2WoHHRe6nYGn0VWMOjv6wE+u\n+0FEioDb0N6rZUAK7b96JrBKRCxg6KRsmdV0BQej9ZDq1AI7NjqmALgmZyMyxpjccEApUFnl3Gaj\nq6oWxmEbdKViF3QGrVU+8O8Ae6LbVT4G3gG2aHRYQfRVjMYHhcDxaEuvBzv+Uky22Myc6fRc6EYA\n/6C+qvhnrP+fEMBcYLj1eTXGdBfl48t7AQ8DwwZV1zz63Jwv16KtuGJor1RBks0W/W0rESkHAuBI\n1p3w8cAAEVmvrdeUkaMKgR+jgeXto6ZO+SxT4zHpsZk50xUsQlvP1OnZzHGzczAWY4zJmYpxFSuA\nbwNj5xcW/BJJXgacDFwKXJ7JQA5ARCpE5Bi0qLCPvuoc3Mxpo4D9o19PaOYYk0U2M2c6PRe6M4Eb\nGjz0KbBeaj66wfdC2zdnjOkORGQb4FvAqyIyubXjM3zvAuAtYAz15UbWApuKyJKGx04ZOWpT4FV0\nP96nwJ6jpk5Jq7uPyQybmTNdQeOmzc0tox5NmvtHjDGmMxORQrTd1i+A8SKybjkmSeyFJH6AJEqy\ndP8aNIu2qsHDxcCTTRxehSZLzAB6s26ShckBC+ZMV7Cw0c+DgNXNHNta9XNjjOkK4uiWkrVoENXj\n62cksRfa/eYq4GEkka0PsS+i3Xagfrm1rInjlgCPR+N8Dt2/bHLIlllNp+dC9xFaMLPOGmAV63/6\nmwrs4ANfhTHGdHEiciiaTfqYiNxX/0Tih2hf6r5oN5zHn+23+3mzSgafifcbfVEy+PrfnfD7RRka\nw5XAhdGPHp2BmwYcJiIz646L+rL2ANaOmjrFAoscK8j3AIxpiQtdX+BL9O/q1tHDC4BhTRw+EjgF\n+GdOBmeMMVkkIk8BTzXx1H/R3qeHAB+moPaT4rJTxqyccR4u5mKkBgJnZWgYdTNzLvq1AE10uJIG\nnSiiAM72yeWJLbOazq4n8E30E9/n0WObop8Om7JJDsZkjDH5I8k1SPIs4MAauOnITTfpNZGPL1tT\nO28A3vt4ZpfcnkJre0J9QAdwtIhckMH7mA6wYM50aj7ws9Eil0OBIqAC/WS4rJlTmttLZ4wx3Ysk\nP9tx+NCXPysq3POD4vjsB8pia94vSTwxv7h/kLFb6FLqkaybeFaX3XpFpu5jOsaCOdOpudA5YMvo\nx8FoS6/X0MCuKVZrzhizIVkBTEzhBn0c32j53K+2dWs/792v7kkR6SUiu4hIacOTXOg2caE7w4Xu\nPy50H7nQndjcDUTkCeD7aNmRhrXnikSkqYQIk2OWAGE6NRe67YG/oL1Xq9Dp/uoGX2XAUdTv/zzQ\nB/6FPAzVGGPy4oIrLhicIvVyz5qem8WJrwBuE5FfisiewE1oO7CPgcNDFw4ELgZOp2GGrLoOrdXZ\nbBcdERkGTKe+7tz2ImIdH/LMgjnT5bnQ7Y72Zf0C+JEPfG0rpxhjTLcRZb3eDfRCZ83uQLNdHweG\no9n/i2/kxqvnu/nXsH4Q19CLwHd84Ne2cL+/A4dHx/5UROz/3DyzbFbT5fnAvwHsnu9xGGNMnkwF\n5qNB2kq0sG9fNLBbCRR7/KPzmf9zWg7kZgC/aSmQi5yLzu6tEREvIhsBvRuWKjG5ZTNzxhhjTBcn\nIpuifVFn78a79+zBpLH3cviPv2TgRhC7IXShA15p5TL/9oE/vY33HQ3ciS7lXisi/2jXCzAdYsGc\nMcYY051IYizwczTJ8U4k+ZQL3e+BS4sLi+nfuz81tTUsWr6I2tQ6K6RX+8Bf2NQlm72VyMnAr9E9\nzKuBcSJSkZkXYtJly6zGGGNMFyIiA9Ei6dNEZH4Th5SgCQop6ttvfQKwcZ+NKS4sxuNZU7WG5auX\nNzyvX8MfRGQX4GDgZRFpblbvOTSZYht0mfYiETlHRJLte3WmPaw0iTHGGNNFiEgBul/tVOASEWmq\nTNObwIPAE8DT0WPvAaR8fb31mpqaxucd50I3ILpPEXAa2jbxJBHp3cyQdkALutcAGwEjqC8ybHLE\nZuaMMcaYriOGdsZZhe5TK0DLNtWTZBXwSKPzpgBrFyxd0KNnSU8qqytZXbVejfUeaBuwEA3O5gND\ngEVoGRK9vMhg4GRgKTAQXV5dER3/Pla8Pedsz5wxJmdc6LYDTkLfNKb5wF+X5yEZ0+WIyLbAPsDr\nIvJBo+diwM5AMfCmiHxdM86FbiIwtpXLf+wDv110rV7AVsBMEfm6646InA7sEt3j/4Bd0WXd7dBu\nPRXo3jlbas0Rm5kzxuTSNkBdP8dT8jkQY7oqEfkYLQLc+PGNgPOBQ4GZwK3oUmudd2g9mBvmQud8\n4L2IrCBanm1kJrAHUIkGjHeKyGbAY0Af4EBgT7Svq8kBC+aMMVnjQncOuhR0O3AGcGmDp/vnZVDG\ndEMiMgYQYEc08WEomgjR0J3Ama1cqhT9t7mwhWOeQwO61SIyV0T6AXuhS7J9o2NuEpFz0eDyPeB8\nEalq8mqmwyyYM8Zk08nAGOD3QLzRc9bT0ZjMGYvuo6tC96+9RKOZsZGbjXw7uTL5VUFBwcAlK5aw\nau2q5q61OS0EcyLi0ZZedX4C7Ivu5auzCfD36DqHAPeifbVNFlgwZ4zJChe6GPVZbY0DOdDlGGNM\nZkxAZ+VeQGfg3qhrsxXtsTupx6Y9jor1ig1wzlFaXMr0udPXyW5tYA90STZdVWgAuBYoQvfP1fXO\nrgGWoBmvJkusNIkxJuNc6OLAu8BOLRzWeAnIGNNOIjIdOAc4S0Rea9Qv9TiP71FTUDMs5mIOIB6L\nUxBvdj7nEhe60jbc/mE0gFuBJj8k0VZii4DfAUeJyJy2vSLTFjYzZ4zpMBe63sC30U/mCXRfzphW\nTvuWC11/H/hF2R6fMRuCFhrefwQcEkvFVqfiqTLvPd57N2zQMKqqqpi1cBaNKlsMQvuv/inNW/dD\nS5+UojNxtcDGaFD3kYh81p7XY9JnwVweuNCNBb6Bpnb3AY7xgdWIMV3aOKCtZUY2Rzds/yzjozHG\nNHS/w03casVWl03rO+2Gquqq3eKxeH+Ho6S4hF4lvRp3ggC42IXuRh/4pWlc/3NgGpp0MQXdv1eG\nfrizGbkcsDpzeeBC9xK6WRS0sOMxPmh644IxnZUL3e3Ah2i1+X8Bo9pxmQd94I/N6MCMMS1yofvD\nsI2HXVJSrDsdFi9fzFfLvmrq0Ot94M9J55pRfbsi4ES0BdgA4G8i8mBGBm1aZHvm8qPhxu8H0EKL\nxnQ1hwN/Bl6mfYEctFz+wBiTHfNmfzWbtZVrWbZyGYXxQmKuyXDgZy50e6dzQRFJichaYCKa8DAZ\neCNzQzYtsWXWHHOhuwMob/DQMeiU9Pn5GZEx7baQjmekzs3EQIwxbfJUra/9w+IVi3v2Ku3FyjUr\nm8tqBbjVhW57H/hmW3SVjy+Po+9lIxjOPUfPPPp8oFpErK1XjtjMXA650JWge+UalmnYDrgsPyMy\npkOe7OD584H/ZGAcxpg28IGfAZy9fPVy5i6aS3JVi123tgROaOWSW6FdJzYFfiIiSQvkcstm5nLI\nB36NC92+6CbRMWi20Ik+8M1WbjSmE3u7g+eP9YG3mTljckREtkBXgva+nMun/ZE/3lPtqo9r5bSv\ngNaSIJYCa9Ckh1kdH6lpK0uAMMa0iwvd5rS/EOjzwCE+8M2VUjDGZJCIjAAuAXZGA64lc5hz/S3u\nlnuBLRodvgi4CHgWmJdOtYXy8eWD0KSHqRXjKqozOnjTKpuZM8a01zy0ynthG887yAf++SyMxxjT\nvL5otulCtPfqjCEM+RQ4DO0csbzB1+c+8MvacvGKcRXz0a0TJg9sZs4Y024udPcDbSkt8rYP/C7Z\nGo8xZn3l48uPjqVip+ywZIe5W6zY4iO0b+sMEVmZ77GZzLBgrhEXuq184D9tx3l7AAegn3h2A+7w\ngb8+0+MzpjNxoTsWuL8NpxztA/9wtsZjjFlX+fjyUnRZtQfaYmvninEV0/I7KpNpls26vgOiN6i0\nudAdjBb//S2a1LALWmfHmO7uQeozUleybt24D4Dbou8XA0daIGdMXhSgvZBLgUPyPBaTBTYz1wQX\nuouB2T7wd7dy3FDgHmCP6KH5wH3AlaS5adSYrs6FLoaW3PkEraEYooVDr0JnAn4M3OoDvyZvgzRm\nA1Y+vvwedG/cauCGinEVYbbuJSL90VIl00TEJjVyxIK5JrjQOXSWbaYP/K1NPD8KzQi6Ft1UCtpQ\neJAP/NqcDdQYY4xpRfn48gOAi9Gl1nMqxlW8357riMhWwCDgPRFZr6SWiBQBf0S3Gy0ALhERy1jP\nAVtmbYIPvPeBvwyIudBdCuBCN8iFbgcXuuuBj4HbqQ/kAP5tgZwxxphO6GV028MCYI/y8eWurRcQ\nkcFoaZMzgNNEpKlrFKJdYfqgGbK92z1i0yYWzLXAB/5moNKF7k20DMNk4OwGhyxEZ+T+B9yY+xEa\nY4wxreoDbA4MRLs5lLbjGiXo3rtBwE+An4lIw25GRLN1r6JdI/oC4zowZtMGFsy1wgf+auBdoKrB\nw28AP0L/Uvf1gd8zao9ijDHGdDZLgBr0PasK2LYd1/gMuANdqn0F3Wo0oInjpqD17AYBJ4rIwPYM\n2LSNFQ1Ogw/82S50s9BPGncCH1tygzHGmK6gYlxFqnx8+TPozNyC6KtNRMQDz4vIpsD+aMLT4iYO\nnQzMBEajs3nHofvLTRZZMJcmH/gr8z0GY4wxpq3Kx5cXoPVPVwCVrFtCqK1uBx4DljeV3CAilSLy\nRyAAlgG2lzwHLJgzxhhjurd9oq8aYBLQ5gSIOtEM3dJWDnsZ7e06AN1DZ7LMSpMYY4wx3Vj5+PLf\noEkJWwJ/rRhX8Uieh2QyzBIgjDHGmO7tKaAa7cn6XJ7HYrLAZuaMMcaYbq58fHkcSFWMq7A3/W7I\ngjljjDHGmC7MllmNMcYYY7owC+aMMcYYY7owC+aMMcYYY7owC+aMMcYYY7owKxpsjDHGmJwQkXLg\n+8CHwAMiksrzkLoFm5kzxhhjTK6cBCSAbwOb5Xks3YYFc8YYY4zJlRloMLcC7d1qMsCWWY0xxhiT\nKzehnSjmi0gy34PpLqxosDHGGGNMF2bLrMYYY4wxXZgFc8YYY4wxXZgFc8YY00W40BU28dg5LnQX\nNPWcMWbDYHvmjDGmC3ChmwDsAYzygZ/hQhcD/gRcFB1SARzuAz8rT0M0pl1ExAGbA7VAJbBSRFbn\nd1RdiwVzxhjTBbjQLQAGAlOA1cAwYKNGh70G7OcDX5Pb0RnTdiLSGzgR2ALYDtgUmAN8BPxWRJbm\nb3Rdiy2zGmNMJ+dC54C+0Y+jgJ1YP5AD+Cbwq1yNy5gO2gPYJfoajX5YGQb0A4bkb1hdjwVzxhjT\n+ZUB6e6JG5fNgRiTQfOAGmA+sAT4Ci0mPBX4NI/j6nJsmdUYYzo5F7odgUlpHv5HH/hLszkeYzJF\nRIajDQyq0fZe74vI8vyOquuxYM4YYzo5F7oTgNvTPLzcB/7DbI7HGNO52DKrMcZ0ftuledxkC+SM\n2fBYb1ZjjOmkXOiKgCOAY9M85bdZHI7JFUkcDZwP/Be4GknW5nlEppOzYM4YYzoZF7rNgNOBU4GN\n0zztHeDRrA3KZJ8kCoG7gGOiR3YFJgIT0jx/EFre42MkuSYLIzSdlO2ZM8aYTsSFbj80KOvdxlMP\n8YF/JgtDMrkgiTJgEVAMuOhRj87OvQbc0GKAJolRwL1AEfAQ8E9gMZJcm8VRm07C9swZY0wn4UJ3\nNPB/tD2QexV4NvMjMjm0F+sHciuBucD2wMhWzt8TKI3O+z5aeHcBkjimxbNMt2DBnDHGdB5XozMr\nbXWvD2yZpYt7HW1l5aOv8cBxQE+09trcVs6fAExHA8AB6AeCXsDNSKL593pJlN12zRA564YtH97h\nP6MP6eBrMHliwZwxxnQCLnRD0f6U7fF6Jsdi8kCSK9AA7HvAICR5EvAU8GvgUiT5VSvnf4omypwL\nLGvwTIut3RbE4z8dWl1z7hErV+2/VXX19eXjyxPtGr5IXETK2nOu6ThLgDDGmM5hq3aetwawciTd\ngSSrgccb/OxpfUau4fmrkMR84EW0tVscOAtJppo7pSyVSuG8dzhX4H0V7YgLoiDuV8AQEblbRJ5r\n6zVMx1gwZ0yGRGUkdgDe9YFv9j9PY5oxAd3nlG5NuTpF1O+zMl2ZJHqhXRCWAQuj4K6N10h+jiR+\nh/by/bC1a/T0/vbiFMXPl5Vs+0lR0a0V4yoWt2PkQ6NxLwYOBCyYyzHLZjUmA6JG6A8ARwMVwEk+\n8O/md1Smq4kSIB5sx6nDfOBnZXo8JocksRXwNDA8euQl4EgkuTJ/g0qPiJQCF6NB3Z0i8kKeh7TB\nsT1zxmRGKRrIAZQDz7vQjcnjeEzX9AgwuR3ntXevnek8vgMMQd+X48BuaHDU6YnIarRg9VkWyOWH\nzcwZkwHREuscNIuszjRgBx94q/Nk0uZCdxgN902l5+/Azy2jtQuTxFjgMeqLRM8CtkOSq/M3KNNV\nWDBnTIa40M0Atmj08Nk+8DfkYzym63Kh+z1waRtP+xfwMx94a/3U2UnCobOpKST5RYPHRwEC9AB+\nhSSnZPrWL7y45Qh0X+bbB+w/I/3kCtOp2TKrMRngQlfA+oEcaEKEMW31G+C6Np7zE2CnLIzFZN63\ngReAF5HEQV8/qsHbD4GjshTI9QIuRPv9XvDCi1taDNBN2B+kMRngA19D0yUEds/1WEz2udAd7kI3\noNFjpZm6frRceh5wa5qnzAT28IGfmKkxmCzRWbk/ojNzw4A/IInN6p9PeiSZrdlVF32lsPf/bsWW\nWY3JgGhmbh7Qv4mnt/eBr8jxkEwWudB9iLZXmgd8hgZdVwE/8IF/KYP3iQO3ASe0cNijwCk+8Esy\ndV+TRdqNYRKaKOWAWrSw7xvAD5Dkwmze/oUXtxyJtgd744D9Z8zO5r1M7lgwZ0wGuND9AG1y3ZRD\nfeCfzuV4TPa40I1Ak1uacj/wo0zvW4tmAfcB9ou+RqEN2K/wgX8nk/cyOSCJ44CbgBLqZ8hSwA1I\n8py8jct0WVY02JjM6EvzSxdTczwWk12/aOG576OzdS0d02Y+8AvR+nMPArjQ9fSB7/T1xzYokhiE\nznhNXSepoWmPo8H4Iej/HXVabL3VYZIoATYB5iDJqqzey+SUzcwZkyEudP8BxjV6eD4wxDIMuw8X\nuheA/Vs57Kc+8DfnYjwmzyRRBuwK/AjYEu2EcDfwbyQ5p4Xz+qN7ao9Cg7oK4NtZ2y8niQLgryyN\n9QAAF4RJREFUMnSv3hTgyqhdmOkGbGbOmMxpqhH2LRbIdTsDWj+Ef7jQPdewK0PUJQSrBdeNaDLD\n/cDOQD+02C/AJcAQJHFqs31RJbkInaFra03B9uqJBnIL0P2ehYDNznUTFswZkzkXAzcDLwOD0PZe\nV+V1RCYb0iniWgQ85UJ3C1rFfxi6z+1HgLV56z56AHsAZWgg5wCPbrcoR2fqpudtdOtKoku7+wH3\n2DJr92LLrMZkmAvd94E+wE02C9O9uND1Ad4GtmrH6TOAMbbXrQvTor5DgU/RAO5o4HT033sBuuct\nhmaofgK8BZxhy5km22xmzpgM84G/34UuZoFctzSG9gVyAO9YINeFaYLDRWj/1O3QgO1NdOatP9rO\n70Lgu8APgN5AcV7GajY4FswZkwU+8E3vkzFd3WtANbrfqK0OdaFzFuR3WQXoMurmaJBWCwxHZ+W2\nBLYBArRP7o7ACGANOpM3q4nrdRnl48sLgN3QjP23KsZV2D7gTsYqQBtjTPpqgSfaee4kC+S6MM1M\n/SfwNLAYLUFzNbo/ts4BwAS0iPTH6D66w3M6zuzYDzgTOBvYM89jMU2wYM4YY9IUBWM/Bp5px+kb\nZXg4JtckORFts/YttIzIvcArDY54LNofVwEsRxNhPsn5ODOvuJnvTSdhy6zGGNMGPvCrXeguRt/Q\nXRtOLcrSkEwuabDWcNn0MHRGLokk346OmYUkLgVKgdYKCHcFz6NbC2qJglcRKQEOjR57SkQsOzaP\nLJvVGGPawYXuefRNPF1X+MBflq3xGJNLInI8cAVaX+9J4HgRsYAiT2yZ1Rhj2mcc8Hkbjn87S+Mw\nJqdEZAzwNzS5oxDYC00EMXliy6zGGNMOPvBzXejirR/5tTeyNhjTfWgtu5+iS7k3Ism1eR5RU85G\ngziPJnl8hBYlNnliM3PGGNN+z6d53HJgWTYHYrLHhS7hQjfUhW7XHNzuDHTGayxa7qQzegcN3pYA\nNwBHiYiVY8ojm5kzxpj2m5Hmcb2AXYDXszgWkwUudPsA30ELAt8HHJe1m0liBDAabf/2GfBl1u7V\nMf8GJgNrReT9fA/GWDBnjDEdcT26V+jCVo5zwLZYMNcVTQe+h/4ZlmTjBiKyA/D94Ry97AQe/jKG\nXwJMRJILWz850RfNqJ0WnZP1JIQo0eGtbN/HpM+WWY0xpp184JPAyDQP3y6bYzFZs4L6WnHfc6G7\n2YWuf4bvcRLQcyabjZ7G8BeBZ4Hb0jz3BrTzxD9pf6s508VZMGeMMR3zaZrHtafQsMkjF7rvA7NZ\nt4vDKcBLLnQ923nNwS50Wzd6eDqQAJe8l+89iCRvQpKLWr2YJBzaSmw1upRvGaUbKFtmNcaYjrkS\nzT4sa+W4VTkYi8kQF7rhwL00XRh6NDDVhW5zYGt0Cb0n8KIP/OwWrvm96JqrXei294GfGz11E/Ai\nMF9EVqQ9SEl6JHEtcDKalDAp7XNNt2JFg40xpoNc6Oaxbo/OpuzuA/9mLsZjOs6FLgE8jtZQa86X\nwOAGPy8CxjQI0nChOxlNlClAZ2frytlc6QN/8XpXlMTewPFouY8HgaVIck2Lg5VEIVCTi/1ypnOy\nYM4YYzrIhe59YPtWDjvKB/6RXIzHZIYLXSFwC3BCG06rQJdNZwAPoDNuzwC9gYMaHHe1D3x94owk\nioGLgF+gLbJ6A6noOlcAD1iwZppjy6zGGNMBLnRbAuVpHHoQYMFc19IHDcTaEsyVU//34aLo16Ob\nOK5+OVUSOwMPobN8rsFXCl3GPRl4n/pEDGPWYcGcMcZ0zEia3lfV2N3ZHojJHBe6LdACvudn6Raz\nGnx/CzCE+gCurgBvDFiDFufVThCSiAE7Rc+9gyRrszQ+04VYMGeMMR2zSZrHzcvqKExGuNA54DTg\nL2hSQ7Zc40I33gfeo8uqtWiANgMYD1QDS4EvgDlIsi742wM4M/r+VuCFLI7RdBEWzBljTMecC8xF\nq+K/B/RH32TrTAEmAnNyPzTTFtEeuYdYtxRJthQA33Whe9rTexxwLZpAcTqSXNrCeXWFiz1QmuUx\nmi7CgjljjOmYfdHluB+je6X+BFQCxcDbwAE+8OmXmzB54UL3DTT5IBeBHGhduEeB6c4t/4kP/P5p\nnvcqkECzYm1WzgCWzWqMMR3mQncrWsUfNLD7AbAf8Fsf+CBvAzMtcqHrAfwDmIDWeivO01AWACN9\n4Jfl6f6mi7MOEMYY03FvNPj+h0CIbmK3fXKd2wC0dMjt5C+QA9gYGJPH+5suzoI5Y4zpuFuB5dH3\n+wLfB24E+uVrQKZ1UbeGeKsH5sYu+R6A6bosmDPGmA7yga9l3dm5s9CMw8K6B1zoNo0yJU3ncgf1\nS+T5sow2tuJyoStxobP3cANYMGeMMZlyWROP/dqF7oDo+5eBb+dwPCYNUWmQx/M4hGXACB/459M9\nwYVuEPA0cErWRmW6FAvmjDEmMz5Aa4M1VAg870I3Ee3demKuB2XS0juP977CB35Ruge70MWB64B9\ngN2yNirTpVgwZ4wxmXEGDZZVGxkLlAFHRLXMTOfSJw/3/AewtQ/81eme4EJXhs7wHhs9VJWNgZmu\nx4I5Y4zJjKeB1pbKCtEK/qZzubD1QzLqfuAcH/jp6RzsQreTC92zwGxgz+jhxcA/szQ+08VYMGeM\nMRngAz8NOAT4TyuHVmR/NCZdLnT90F6nuTIJODHaq9cqF7qT0A4iBwF9gRXAxcAoH/gPsjZK06VY\nMGeMMRkSZbWeEn0taeaw0bkbkUnD34BtcnSvlcAxPvBr0jnYhe5ctOxN3Xt1CviOD/yVPvALszRG\n0wVZMGeMMRnkA5/ygb+V5ktN7JzL8ZjmRfsXc1nf7Rc+8DPTOdD9f3v3GmxXWd9x/PuchJOLMZGB\nAEVIEBNKxKDcCp0iUrmIzIiaAR2KlKIFHQsvBBF80a6zsFA7LdgWSlFhBjHWqZUWnCrFW6UgVO4x\nhYAQQgKYEEAI5HrOyXn64tmn2dnZe5999tmXrLO/n5kzyV5r7bX+mbw4v3nW8/yfPCwmjcCVuy1m\n8Z7Wl6WiM8xJUouV+sn11zi9qJO1qLaYxSHgWqDexvYTdR+wBDg3ZvHmRr4Q8nApcC+wf8Wp/21x\nbZokDHOS1HoHAifUOHduaVN37QZiFr8OXNim278JXBSz+O8xi0vH8b2DqN4uJQt5+GxLKtOkMrXb\nBUjSJFSvZcQ0UhuTdgUIjd/DpZ9WL4T4MfC5kIe5pMGTLcAzwKPAOuCJmMVqcytrLY7oAy4Pefh5\nzOKTLa5VBRZiYwtqJEkNCnnoJ70SW1jnshOc/7R7CXmYTwpg9f7fxuMx4L11zq8D/h744ejK1JCH\necAPqL9Q5k3gC6VRRcnXrJLUajGLg8CJwH/XuSzvTDVqRMjDsaSGvK0KcgAbSHPmatkEXAksC3n4\nWml3h8sYe8XzW4EbQx4+15oyVXSGOUlqg5jF35CavN5DGoGptF9nKxIAA3P2ZGDOgQzMCRVnTgfm\nt/hp7weOpfpr0ydJO0+M7ghyIanx9DPATaQgWE8g9Z2TDHOS1EbvBN5H+qVb2Vvsts6X0+MG5hwN\nLAW+Cnyw8ixwaxueOgX4dcWxbcB0YK+K46eQ+t5dBcxroJ41rShQxWeYk6T2ua705whp4UO5Wq1L\n1Aar/3Kv/gem9X/lxSlTjhxM7WGOAGBgTmBgzrExzj7r/jjzCuDnbXh8ZZD/JWnFajWDwOqYxTdI\nr2BrtSO5Bfh2K4pT8bmaVZLaZ7S9xMukkZZyp7JrU1i1yfm/s8+ieYNDB8+IzN5/eGjG6Zu2/PSo\n9Kr1gggXb4fnj2PqO4BPAE9TvTVINcPAWmBOje9E4OCyz49Su20NwPOjW33FLK4MeTiCNFr3ydIz\nRq2NWRxpsEZNcoY5SWqf0dG3ecBv2LkJ7MaQhwNiFl/ofFm9ZfE3F89m6tRzftvXN70/xk0Phmkv\nfnfO7GnLV63Z6+7p08766732XNAHCz/9+htPx8s2rA95uJc0h66eVcArpFG+A0vH1gDPkf7fA/AW\n0rZuo+EtAjPGuO9Oo3gxi8PARaWtvT5VeubrpMUTEmCYk6R22qPs7y+wc5gbAa4hjQSpvY4G9t/e\n1/fcljR6towUrt+8fs+3LVwwNNR/5NZt4Z4Z04/7WLp+ewP3HAGOqTg2j11HYMv9Ajh+jPseEvKw\nR2l3iv9XGoW7qYG61IOcMydJ7VP+y/5odkyE3wgcDpzc8Yp60PD24Ze2bNsyP8b4NJABly8/b/lK\nBjZse62vb83Jm7aEvhg5682N8/92YPos4LAxbvkwaXHLeGwBFjRwXT/wjnHeWz3OkTlJaoOQh5nA\nGWWH+kgtSqaW/n4QqT2F2mzFp1Y83n9V/7QQwqLBocFvxSy+NHru5M2brx2GI+cPDfO7g0Nr3se2\nq9l5jls1Q2Ocr+ZB6s+VK3cUu66AlWpyZE6S2uMwdp0fdQCwLztWMr7eyYJ62dDw0B2DQ4PHAD8K\neRgIeZgNcMVrG37w0U2bvjR/6+a7PxE3xu2Bi8e41eOk3nHjNZ7Vy5VtU6S63M5LktqgtKXXMuDQ\nMS79/ZjF/+lAST0t5OFI0uvRUY8A9wObgTNp/NXmQ6RX5uN1J/ChBq99JWZxbhPPUI9yZE6S2qC0\npdfZ7NpjrNKiDpSjtE/qAGm+IqSFCqeRts9qNMg9SXNBDlKT4EatbPIZ6lGGOUlqk5jFx4Arxrjs\nnJCHsUbvNEExiyMxizlwKak33ArSIoZhUruPml8lrVx9noltn/WHNB7S/nkCz1EPMsxJUntdD9xQ\n49yvgBNL16gDYha/TtpZYT92vGbdG3gCeKni8nWkOXJPkhY97DvBxzfS8gTas62YJjHnzElSB4Q8\nLAG+CcwqO7ySHS0uLohZtI9Yh4Q8LAfeXXF4PWkE7nDgPuA4dt2GbSKeZeyVsiPAPjGLr7bwuZrk\nDHOS1CEhD6cCd5U+vsaur+1Oj1m8s7NV9Z6QhwNIoa2WjaTdHAarnLuONP/tUFID4sXAkXXutZU0\n+rcemM/YO0AAfB/4mNt1qVH2mZOkzlkNnAUsJe3XWhnmPkha9aj2iqQwd2CN87OAd9U493DM4rLy\nAyEPxwD/wo6FFM+Stt5aBrwRszgS8rCQxnvHnQEsDXk4r3InCKka58xJUofELD4Vs/g94E8rTm0l\nhYfPd76q3hOz+CJwcxNffZY0z7Hyfg+SXsneClwLHB6zeHfM4utlo2vD43zW2cCSJmpUD3JkTpI6\nbxVwSNnnDTGLK7pVTI+6g7RX6gbSApXZpP+TzaSFCk8AjwK/BywktTa5LGbV5ybFLK4Hzqv1sJjF\nVSEP3yGFtEatHse16mHOmZOkDgt5mA88V3ZoBJjuK7XuCnnYm/RadLDi+Axga60gN477zwTuBY5o\n4PJ7YhYb3f5LPc6ROUnqvLWkeVuh9PlGxv8aTi0Ws1i131zM4liNnxu9/+aQhzNJc+emjHH50lY8\nU73BOXOS1GGlkZ9vkObOvQu4aKKjPiqMdTT2u/fxdheiycOROUnqgpjFz3S7BnXFNtIiiveMcd3b\nO1CLJglH5iRJ6pCYxe3AuaR5kvW8vwPlaJIwzEmS1EExi8uBfxrjslMrD4Q8hJCHU0IeFrSnMhWV\nYU6SpM67HHi6zvm9R/8S8nBSyMP1pJY2PwIeC3n4gzbXpwKxNYkkSV0Q8nA8cE+dS/YCTgK+W+Xc\neuComMUX2lGbisWROUmSuiBm8V7SNmC1nEjaz7WafYBfhjwc3Oq6VDyGOUmSuufzQK0+dqcAy+t8\nd3/gH0MeQp1r1AMMc5IkdUnM4lrSfq7VfBi4j9TOpJbTgEWtrkvFYpiTJKm7rmbn7d1GvZ00b+7e\nMb7/gVYXpGJxAYQkSU0KeZgFzAbWxyw2vSVbyMOpwF1VTl1Ceg1br5XJJuCEmMVHmn2+is0wJ0lS\nE0IeLgX+ghTmIvAKabuu0Z+1MYuXj+N+1wEXVRx+BngvsBLYt87XXwZOj1l8qOF/gCYNX7NKktSc\nTaQgBxCAucBi0sKFc4Ht47zfZcBjFccWACcDd4zx3bnAAyEPD4U87DHO56rgDHOSJDXnW8DrNc7d\nBwyM52Yxi1uBP2LXEPgV0mvWsV6lBeAoarcz0SRlmJMkqTlvBWqNgt0fszg43hvGLK4AflZx+FBg\nIfBXDd5m5nifq2IzzEmSelppz9NmerVdDLylyvGngS9OoKTzgZuAkbJjfwNcQ2OBbmgCz1YBTe12\nAZIkdVLIw97A3wHTSWFsMelV5vXjvFW115kvAKfELI5UOdeQmMUXgQtCHpYDXyUNvMwH/ov0GnYB\ncFadW7zR7LNVTIY5SVKv+VfSVlmjIrC0ifvsU/H5VeDUmMXVTda1k5jFfwh52AbcWDp0OPAAKdBt\nAz5Z46sHAC+2ogYVg69ZJUk9IeRhSsjDn7NzkAO4HdjYxC03VXzOS3PeWuk24PmyzzNJ9f4KuBCo\n1ttuzxbXoN2cI3OSpEkp5GEmcDywhNSrbT6wX5VLv9xkw98lwBOkBQoAv22mznpiFl8JeTge+DfS\nStVRVwOnk0bplgL9ZefKw596gGFOkjRZje6cMJe08nSQNJK1mdRk9wbg4JjFR5u5ecxiDHn4MPBO\n4CR27REHQMjDHNKq18OBR0gjeiMxiw31oYtZXBPycBxpnt+flQ5PBb5PCqcfAP4TmFU6twh4vJl/\nk4rJHSAkSZNWabutQeAQYBWwldIq0Zi17hdgyEOodr+Qh4OAW0grTJ8CPgKsB/4kZnH5OJ/RRwqg\nnykd+hlwcilUnsOOeX8rgPOAx2IWXdnaAwxzkiS1SCk8fhw4iDQ6thH4D9JWX7NIoe524PxGR+Yq\n7t8HXAecDRwVs7iqdDwAPwROK7v8J8CZMYsbmv33qBgMc5IktUDIwwLgp8C8ssPLSj9TgHOAK2MW\nsxY8a1bM4saKY3OB1cCMssNfiFm8ZqLP0+7N1aySJLXGzewc5ADeQ9qe68DS54WteFBlkCsde5k0\nGjdqCPh2K56n3ZthTpKkCSo1Ij6hxuklwI9JPeK+1OZSbi37+yUxi+va/DztBgxzkiRNXH+dc9NI\nr1/PaFVD4Tp+UfrzqpjF8e5ooYKyNYkkSRO3lrSKdFGVcz+JWby/Q3W8VKploEPP027AkTlJkiao\n1JbkQlJvu3IvA5d0sJRpwEebbIKsgnI1qyRJLRLysJDU2PcgUmuS62MW13a1KE16hjlJkqQC8zWr\nJElSgRnmJEmSCswwJ0mSVGCGOUmSpAIzzEmSJBWYYU6SJKnADHOSJEkFZpiTJKnAQh5CyMP8bteh\n7rFpsCRJBRLyMBM4GhgErgV+DfwxcBnwBHBXzOJI9ypUpxnmJEkqiJCHjwDfA6bWuewa4MsxixtC\nHqYB745ZfLgjBaorDHOSJBVEyMMdwBkNXPp46edE4E1gYcz8hT9ZOWdOkqTi+CIw3MB1hwEfB/YB\nXm1rReo6w5wkSQURs/gUcMM4v3a7o3KTm2FOkqRiuRIYavDaN4BvtLEW7QYMc5IkFUjM4qvAnQ1e\n/rWYxVfaWY+6zzAnSVLxfBZYO8Y120krXzXJuZpVkqQCCnn4NHBT2aF1wMqyn2eB78Qsbu9Ceeqg\nen1qJEnS7usW4GVgFfBszOKm7pajbnFkTpIkqcCcMydJklRghjlJkqQCM8xJkiQVmGFOkiSpwAxz\nkiRJBWaYkyRJKjDDnCRJUoEZ5iRJkgrMMCdJklRghjlJkqQCM8xJkiQVmGFOkiSpwAxzkiRJBWaY\nkyRJKjDDnCRJUoEZ5iRJkgrMMCdJklRghjlJkqQCM8xJkiQVmGFOkiSpwAxzkiRJBWaYkyRJKjDD\nnCRJUoEZ5iRJkgrMMCdJklRghjlJkqQCM8xJkiQVmGFOkiSpwAxzkiRJBWaYkyRJKjDDnCRJUoEZ\n5iRJkgrMMCdJklRghjlJkqQCM8xJkiQVmGFOkiSpwAxzkiRJBWaYkyRJKjDDnCRJUoEZ5iRJkgrM\nMCdJklRghjlJkqQCM8xJkiQVmGFOkiSpwAxzkiRJBWaYkyRJKrD/A+OCx7RcGQ/uAAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = protected_areas_utm.plot(figsize=(10, 10), color='green')\n",
    "data_utm.plot(ax=ax, markersize=5, alpha=0.5, column='mineral1', legend=True)\n",
    "ax.set_axis_off()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Spatial operations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " \n",
    " <ul>\n",
    "  <li>Access the geometry of the \"Kahuzi-Biega National park\".</li>\n",
    "  <li>Filter the mining sites to select those that are located in this national park.</li>\n",
    " </ul> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "kahuzi = protected_areas_utm[protected_areas_utm['NAME_AP'] == \"Kahuzi-Biega National park\"].geometry.squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pcode</th>\n",
       "      <th>vid</th>\n",
       "      <th>project</th>\n",
       "      <th>visit_date</th>\n",
       "      <th>name</th>\n",
       "      <th>workers_numb</th>\n",
       "      <th>interference</th>\n",
       "      <th>armed_group1</th>\n",
       "      <th>mineral1</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>661</th>\n",
       "      <td>codmine00680</td>\n",
       "      <td>1032</td>\n",
       "      <td>IPIS - PROMINES MoFA 2013-2014</td>\n",
       "      <td>2013-08-28Z</td>\n",
       "      <td>Ibozia/Kalumé</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (567832.7086093378 9759143.339360647)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>662</th>\n",
       "      <td>codmine00681</td>\n",
       "      <td>1025</td>\n",
       "      <td>IPIS - PROMINES MoFA 2013-2014</td>\n",
       "      <td>2013-08-26Z</td>\n",
       "      <td>Matamba</td>\n",
       "      <td>150.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (598323.5389475008 9758688.142411157)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>663</th>\n",
       "      <td>codmine00682</td>\n",
       "      <td>1031</td>\n",
       "      <td>IPIS - PROMINES MoFA 2013-2014</td>\n",
       "      <td>2013-08-27Z</td>\n",
       "      <td>Mutete/Mukina</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (570733.4369126211 9761871.114227083)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>664</th>\n",
       "      <td>codmine00683</td>\n",
       "      <td>1033</td>\n",
       "      <td>IPIS - PROMINES MoFA 2013-2014</td>\n",
       "      <td>2013-08-28Z</td>\n",
       "      <td>Mutete</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (569881.0930415759 9762219.110778008)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>codmine00779</td>\n",
       "      <td>1603</td>\n",
       "      <td>IPIS - PROMINES MoFA 2013-2014</td>\n",
       "      <td>2014-02-25Z</td>\n",
       "      <td>Mazankala</td>\n",
       "      <td>120.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (613075.5326777868 9722956.979837928)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>813</th>\n",
       "      <td>codmine00833</td>\n",
       "      <td>2439</td>\n",
       "      <td>IPIS - IOM PROMINES 2015</td>\n",
       "      <td>2015-07-28Z</td>\n",
       "      <td>Kitendebwa</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>FARDC</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (693078.9282059025 9770107.517721133)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871</th>\n",
       "      <td>codmine00893</td>\n",
       "      <td>1226</td>\n",
       "      <td>IPIS - PROMINES MoFA 2013-2014</td>\n",
       "      <td>2013-09-28Z</td>\n",
       "      <td>Sebwa-Lukoma</td>\n",
       "      <td>130.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (660406.3452248175 9715261.717041001)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>codmine00894</td>\n",
       "      <td>1305</td>\n",
       "      <td>IPIS - PROMINES MoFA 2013-2014</td>\n",
       "      <td>2013-10-30Z</td>\n",
       "      <td>Rwamakaza</td>\n",
       "      <td>160.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (661266.834456568 9716072.198784607)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1486</th>\n",
       "      <td>codmine01764</td>\n",
       "      <td>180</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>Mugaba I</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (685167.3714990132 9744069.967416598)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1487</th>\n",
       "      <td>codmine01765</td>\n",
       "      <td>181</td>\n",
       "      <td>IPIS - 2009</td>\n",
       "      <td>2009-01-01Z</td>\n",
       "      <td>Mugaba Ouest</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Or</td>\n",
       "      <td>POINT (683156.6865782175 9746324.416321497)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1681</th>\n",
       "      <td>codmine01997</td>\n",
       "      <td>2476</td>\n",
       "      <td>IPIS - IOM PROMINES 2015</td>\n",
       "      <td>2015-08-02Z</td>\n",
       "      <td>Nguba(Nkuba) kamisoke</td>\n",
       "      <td>122.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Raïa Mutomboki</td>\n",
       "      <td>Cassitérite</td>\n",
       "      <td>POINT (622151.3489110788 9808363.111073116)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             pcode   vid                         project   visit_date  \\\n",
       "661   codmine00680  1032  IPIS - PROMINES MoFA 2013-2014  2013-08-28Z   \n",
       "662   codmine00681  1025  IPIS - PROMINES MoFA 2013-2014  2013-08-26Z   \n",
       "663   codmine00682  1031  IPIS - PROMINES MoFA 2013-2014  2013-08-27Z   \n",
       "664   codmine00683  1033  IPIS - PROMINES MoFA 2013-2014  2013-08-28Z   \n",
       "760   codmine00779  1603  IPIS - PROMINES MoFA 2013-2014  2014-02-25Z   \n",
       "813   codmine00833  2439        IPIS - IOM PROMINES 2015  2015-07-28Z   \n",
       "871   codmine00893  1226  IPIS - PROMINES MoFA 2013-2014  2013-09-28Z   \n",
       "872   codmine00894  1305  IPIS - PROMINES MoFA 2013-2014  2013-10-30Z   \n",
       "1486  codmine01764   180                     IPIS - 2009  2009-01-01Z   \n",
       "1487  codmine01765   181                     IPIS - 2009  2009-01-01Z   \n",
       "1681  codmine01997  2476        IPIS - IOM PROMINES 2015  2015-08-02Z   \n",
       "\n",
       "                       name  workers_numb  interference    armed_group1  \\\n",
       "661           Ibozia/Kalumé          80.0           1.0  Raïa Mutomboki   \n",
       "662                 Matamba         150.0           1.0  Raïa Mutomboki   \n",
       "663           Mutete/Mukina         170.0           1.0  Raïa Mutomboki   \n",
       "664                  Mutete         100.0           1.0  Raïa Mutomboki   \n",
       "760               Mazankala         120.0           1.0  Raïa Mutomboki   \n",
       "813              Kitendebwa          50.0           0.0           FARDC   \n",
       "871            Sebwa-Lukoma         130.0           1.0  Raïa Mutomboki   \n",
       "872               Rwamakaza         160.0           1.0  Raïa Mutomboki   \n",
       "1486               Mugaba I          50.0           NaN             NaN   \n",
       "1487           Mugaba Ouest          46.0           NaN             NaN   \n",
       "1681  Nguba(Nkuba) kamisoke         122.0           1.0  Raïa Mutomboki   \n",
       "\n",
       "         mineral1                                     geometry  \n",
       "661   Cassitérite  POINT (567832.7086093378 9759143.339360647)  \n",
       "662   Cassitérite  POINT (598323.5389475008 9758688.142411157)  \n",
       "663   Cassitérite  POINT (570733.4369126211 9761871.114227083)  \n",
       "664   Cassitérite  POINT (569881.0930415759 9762219.110778008)  \n",
       "760   Cassitérite  POINT (613075.5326777868 9722956.979837928)  \n",
       "813            Or  POINT (693078.9282059025 9770107.517721133)  \n",
       "871   Cassitérite  POINT (660406.3452248175 9715261.717041001)  \n",
       "872   Cassitérite   POINT (661266.834456568 9716072.198784607)  \n",
       "1486           Or  POINT (685167.3714990132 9744069.967416598)  \n",
       "1487           Or  POINT (683156.6865782175 9746324.416321497)  \n",
       "1681  Cassitérite  POINT (622151.3489110788 9808363.111073116)  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mines_kahuzi = data_utm[data_utm.within(kahuzi)]\n",
    "mines_kahuzi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(mines_kahuzi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Applying custom spatial functions\n",
    "\n",
    "Shapely and GeoPandas provide a lot functionality out of the box, because sometimes they will not exactly fit your analysis needs. However, we can still easily use them as building blocks for a custom spatial operation, and apply this to all our geometries. \n",
    "\n",
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>: Determine for each mining site the \"closest\" protected area:\n",
    " \n",
    " <ul>\n",
    "  <li> PART 1 - do this for a single mining site:\n",
    "   <ul>\n",
    "    <li>Get a single mining site, e.g. the first of the dataset.</li>\n",
    "    <li>Calculate the distance (in km's) to all protected areas for this mining site</li>\n",
    "    <li>Get the index of the minimum distance (tip: `idxmin()`) and get the name of the protected are corresponding to this index.</li>\n",
    "   </ul> \n",
    "  </li>\n",
    "  <li> PART 2 - apply this procedure on each geometry:\n",
    "   <ul>\n",
    "    <li>Write the above procedure as a function that gets a single site and the protected areas dataframe as input and returns the name of the closest protected area as output.</li>\n",
    "    <li>Apply this function to all sites using the `.apply()` method on `data_utm.geometry`.</li>\n",
    "   </ul> \n",
    "  </li>\n",
    " </ul> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "single_mine = data_utm.geometry[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "dist = protected_areas_utm.distance(single_mine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Virunga National park'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idx = dist.idxmin()\n",
    "closest_area = protected_areas_utm.loc[idx, 'NAME_AP']\n",
    "closest_area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "def closest_protected_area(mine, protected_areas):\n",
    "    dist = protected_areas.distance(mine)\n",
    "    idx = dist.idxmin()\n",
    "    closest_area = protected_areas.loc[idx, 'NAME_AP']\n",
    "    return closest_area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "result = data_utm.geometry.apply(lambda site: closest_protected_area(site, protected_areas_utm))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Using spatial join to determine mining sites in the protected areas\n",
    "\n",
    "Based on the analysis and visualizations above, we can already see that there are mining sites inside the protected areas. Let's now do an actual spatial join to determine which sites are within the protected areas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mining sites in protected areas\n",
    "\n",
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Add information about the protected areas to the mining sites dataset, using a spatial join:\n",
    "   <ul>\n",
    "    <li>Call the result `data_within_protected`</li>\n",
    "    <li>If the result is empty, this is an indication that the coordinate reference system is not matching. Make sure to re-project the data (see above).</li>\n",
    "      \n",
    "   </ul>\n",
    "  </li>\n",
    "  <li>How many mining sites are located within a national park?</li>\n",
    "  <li>Count the number of mining sites per national park (pandas tip: check `value_counts()`)</li>\n",
    "\n",
    " </ul> \n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "data_within_protected = geopandas.sjoin(data_utm, protected_areas_utm[['NAME_AP', 'geometry']],\n",
    "                                        op='within', how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data_within_protected)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Itombwe Nature Reserve          21\n",
       "Luama-Katanga Hunting Domain    14\n",
       "Kahuzi-Biega National park      11\n",
       "Luama-Kivu Hunting Domain        9\n",
       "Okapi Faunal Reserve             5\n",
       "Maiko National park              3\n",
       "Tayna Nature Reserve             1\n",
       "Name: NAME_AP, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_within_protected['NAME_AP'].value_counts()\n",
    "# or data_within_protected.groupby('NAME_AP').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NAME_AP\n",
       "Itombwe Nature Reserve          2987.0\n",
       "Kahuzi-Biega National park      1178.0\n",
       "Luama-Katanga Hunting Domain     930.0\n",
       "Luama-Kivu Hunting Domain       1057.0\n",
       "Maiko National park              493.0\n",
       "Okapi Faunal Reserve             997.0\n",
       "Tayna Nature Reserve             244.0\n",
       "Name: workers_numb, dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_within_protected.groupby('NAME_AP')['workers_numb'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mining sites in the borders of protected areas\n",
    "\n",
    "And what about the borders of the protected areas? (just outside the park)\n",
    "\n",
    "<div class=\"alert alert-success\">\n",
    " <b>EXERCISE</b>:\n",
    " <ul>\n",
    "  <li>Create a new dataset, `protected_areas_borders`, that contains the border area (10 km wide) of each protected area:\n",
    "   <ul>\n",
    "    <li>Tip: one way of doing this is with the `buffer` and `difference` function.</li>\n",
    "    <li>Plot the resulting borders as a visual check of correctness.</li>\n",
    "   </ul>\n",
    "  </li>\n",
    "  <li>Count the number of mining sites per national park that are located within its borders</li>\n",
    "\n",
    " </ul> \n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "protected_areas_border = protected_areas_utm[['NAME_AP', 'geometry']].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "protected_areas_border['geometry'] = protected_areas_border.buffer(10000).difference(protected_areas_utm.unary_union)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd728f47518>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/rn1/FwNCPJjWz+JsDmaUMjSs40tTtAXF0SgoNMFH21NZG5fJ9/eOI7NEy2/H89iRVITB\nZKaXvxufLhxJj3pZ3QB/nsxnWJgXw8O8rWZXhJ8rr84dwnM/n2BkhA9ag4mN8Xl8s2Sc1d6zPVAc\njYJCPYo1NSxaFUdBRQ1fLR5DTx8X+gV6NFiqNIWUki/3ZfLojD5WLdkJcEn/AP44kc+V7+ykRKPn\nkpgebIzP483fy7lvanRdGdHORItRJyHECiFEgRCiyW1tYeFtIUSyEOKoEGJ4bftQIcRuIUR8bfuN\n9casFEKkCSEO175an9+uoGBFvj+Yjcks2fr4lAYh4ZZILaqisFLH1H4BVrQOjmWV89BXh9mSkE9p\nlR6zlOxJLSYxvxJXBzve35pi1fc/X1ozo1mJpSbwqmauXwb0rn2NxiIENxpL/eD5UsokIUQwcEAI\nsVFKWVY77nEp5bcXYryCQnuSXabl3S3JfH33GOzbcJhNSsmnu9KY1Mff6rOZj7anUK418OrcIfi7\nO3K6uJpZAwMRQpBTpmXm0u2UVxvwdOlc0r/WVKpMrHePHCFEAeAPlDV3IwUFW7LxuKU8Z79AD6SU\nSEmjiNOJnAqOZJUxINiDlEINxRo9FVoDO5KK+ObusVa38Y4Jkdy+Yh+ZpVqm9A1osEwK9nJmYm8/\n3vkziX93ULJka7G2UiUAQohRgANQf173ohDiv8Bm4MnmVBAUpUqFjqKgsoZDmaWMevEPKnVGTFIy\nNNSLgSGeBHg4ciSzjP3ppYyO9OGVDacI9XZmSE8vyqsNvHfL8AYlP63F8DBvpvQNoLrG2OT1/14V\nw8yl25k/NoIwX+ue6WkL1laqRAgRBHwOLJBSmmubnwLysDifZcATwHNN3VxRqlToKB6Z0YdJvf0I\n8HDC09kelYBDp8s4lVdBbpmWXv6uvHb9ENwc7TCYzNipRJsKgV8omSXVfHMgi/icckZGNB3ZCnB3\nQqs3YW/XcXa1BqsqVQohPID1wL+llHvOdJBSnpnt1AghPgUeawc7FBQuCAc7FeOi/Rq0XRLTg0ua\niDi1ZQ+nPSio0HHdB38xobcfQggMJonOYGpUFF0lYESENx9vT6tTf+gMWFOp0gH4Acv+zTf1B9Tu\n4eTWis/NBjp3ooaCgo35bHc6A0M8efOGcwdohRC8ddMwLnlzG1P6+jOpT+cQJG9NeHsNsBvoK4TI\nEkLcKYRYIoRYUtvlVyAVSAY+Bu6tbb8BmATc3kQYe7UQ4hhwDIsC5gvt90gKCt2PYo2ecVFNy/Ce\nTQ8PJ96+eRj3rT5IQWXHlOpsCWsqVX4BfNHMmGmtNVBBQcFCW5ZrU/sGML1/AK/9lsBr1w+xolWt\nQykToaDQTbl0QCCJ+ZW2NgNQHI2CQrdlYIgnCYqjUVBQsCa7U4qJDbdegmdbUJIqFRS6Ge9vTWbL\nqQLicyr41+X9bW0OoDgahQ7CbJZklFRjpxKYpeRIVjkanZEof1dGRvg0Ouqv0JhqvalV/TJLtEgJ\nP90/gegANytb1ToUR3MRkVyg4ZejOcyMCSQm2KND33vOB3+RVlSFSoDOYGZoTy88ne35YFsyFVoj\nD0yL5s4JkR160rYrMT7aj2d/PsHYKF+G9jx3kaupff05mVvRaZwMKI7momF7YiFLvjjAtH4BfPbX\nHm4bG8HDl/TukA92pc7A8exy1j84kb6B7g3KY5rNklN5ldz9RRx6k5l7p0Rb3Z5zkVlSzZp9p8mv\nqCEqwJVLBwQS5W/7D+xVQ4LZklDA1/szGdrTC02NETfHxh/f5TvTePW3U8wZ3nGaTa1B2Qy+CJBS\nsnpvBgvHR/DuLcNZvWgM721Jplxr6JD3f21jAjNietA30B1omBGtUgligj34bOEo3tiUiM7QuuVB\ne3PwdCmz/redy9/eQbFGT5CnE6dyK7nniwMYTeaWb9ABjO3ly67kIu778iD//PZIo+vrj+by/pZk\n3rhhCC/PGdTq+xZraqz+u6DMaC4CdqcWsye1hH9c0geAz/ekM6aXD14uDlZ/75O5FfxyNJff/jHx\nnP0OnS6jbw93HO1s89334vqTXD+iJ7eNCceh1gYpJXM++IsfD+dwXaztZwjXDQ/F1dGOjOJq3t6c\nxI0f7SarVFt3vUpv5M0bhtTVEm6JU3kV7Esr4bXfEnByULPt8Sm4WKnIueJoujmphRqW/p7IjJge\n9A/yIL9Cx89Hctn1RMcczq7QGqgxmPhgawpje/kyI6ZHo+WalJJP/0pj4fgIm+zRGE1mEvMrefeW\nYXVOBix5Q9cOC2FnclGncDQqleDyQUEABHs5Ua41MC7KDyEs0i++rg74ujm26l770kpY9Nl+YoI9\nWDIlim0JhXyxJ4PFk6KsY7tV7qrQKTiQUcpV7+ykb6A7z149AIAjmWXEBHl0WAW20b18+faecZjM\nkmd/PsFV7+6koKJh/k1KYRUZxdVcNSS4Q2w6m4Ony/B0tietqKrREmJgiCfxOeU2setcXDM0hPlj\nI4gOcCPK340+Pdxb7WTMZsnynalcFxvKmrvGMD7aj7TiKqvuRSkzmm7MruQiJvf154XZf6/Xfz6a\ny6Q+fucY1f70D/LguWsG8q/LTTz/ywkmvLqFubGhXDc8hBM5Fbyw/iQPTu/dqORBR9HTxxlnezWP\nf3OUQE8n1tw1pm5mE+7jUhsult0iIpZVWs1/1h0nt1zH87MH8sjaI/x2PI/5Y8OZZsV6x8qMphvT\nO8CN7HpreIDCSh39Ajs2tH0GJ3s1L147iD8fnYwAHlxzmFW7M1h791jum2q7aFOQpzO/PzKZ7f+c\nio+rA5e9tZ0fD2dzLKucPaklGM1m9J1kQ/hCSCuqYubS7Xi7OrDmrjFUaA38cSIfndHEmn2nKahs\nsshlu6DMaLoxdmoV2WW6BuFkrcFss5nDGUK9XXjx2tZHRToKtUqw7LZYfjqSw/cHs8ku0+Jsr+aT\nBSOtpjzZkbg72aEzmHjmygG4OqrxdnXgjRuGEO7ryr2rD5BcoGmkVdVeKI6mG1NapSfU2xmTlKgQ\nSClJyKugf5C7rU3rtAghuGZoCNcMDbG1Ke1OSZUeBzsVyYUaFn66j3ljwvnnrH68tyUZRzu1VfOi\nlKVTN2XLqQJe25TAdbGhdXVM8itqUAmBj6v1w9rWorzawPcHs1h/NJdqfdMFuhWa5tNdaSya0Ise\nHo7oDGbWxmVRrKnhvS3JLJsfa9WZbqsczfmKyNVeWyCESKp9LajXHiuEOFY75m3RHXbaOglpRVX8\n4+vDvHH9EG4bE17XvjYuk6n9ArrspqaUkpc3nOSTHWm8tyWZp3+4uCrAFmtqyCypplpvrJWDaVut\nfrMZvFzsCfV2Ydn8WFQCfj2WS2y4N6He1lVMaO3SaSXnISInhPABngFGYFFGOCCE+ElKWVrbZzGw\nB0s50FnAhvN7DIX6LNueyi2jwxrUizWYzHxzIJOXrx1sQ8sujM/3ZLD+WC6vzR1CTJAHV7+3s9tE\ng85FckEly3em8euxPADKtQbCfFzILdcS6u1CTJAHY6N8mVfvS6UpwnxdSCmsAiyKl6XVet78PZFH\nZvSx+jO0ytGcr4gcMAX4XUpZAiCE+B2YJYTYCnhIKXfXtq/CUqRccTTtwPbEQj5ZMKJB2+8n8nF3\ntG913dnOiFZvYkb/HswaGEi13kiF1kC13oRrEzk/3YXsMi2LPotjQLAnXy0eQ+8AN3LLdXx/MJs5\nw0NILariQEYpb29OatHRDAj2YGN8HlJK9CYzJrPktblDmN7fujK+0H6bwc2JyJ2rPauJ9kYoAnJt\no1pvJLdc2yh6sDO5iFkDA7t0OYarhwYz483tPPz1YYxmSYSva5d2MgaTmZIqfZORHrNZ8vS6Y/x4\nOIcofzcWjo+gf5DlWEJPHxceuqQ3AKHezry/JZkJ0ec+G2U0mTmWVc6JnAryK2p4dGZfskq1xOdU\nNCkn09601/9ScyJybW1v3KgIyLWJHw5lM7mPf4MN351JRaw/mst394yzoWUXTpCnM6vuHMWp3Eoq\ndAYWjo+wtUnnTbGmhpuW7SGrVEtMsAf/urw/8TnlrDuUTUJeJSHezuSW69j86GSCPJ0bjTeZJT8d\nyeZoZjkncisordbz2DdHePry/ng3sdm/I6mIr/ZnMirSh0BPi2MTgJtTxzjq9nqX5kTksrAsn+q3\nb61tD22iv8IFkluma1BrJqO4intXH+DdW4Z3qvok58vwMG+Gh3WO8pQXwuubEhkV6cOGhwbwyc40\nFn22n9hwbxZN7MWgEE+OZJXh4+LQyMmYzJK7P48jPqcCJ3s1Uf6u6I1m7pwQyR8nC5j+5jYGhXhy\nOLOMF2YPrEvrMNQuleaPjai7V16FjisGB3XI87aXo2lORG4j8JIQ4sxvxkzgKSlliRCiUggxBtgL\nzAfeaSdbLmo8ne1JKdQAkFOm5eZle7h3anSnERJTsCCl5HBWOUazZMnkKO6e1KvBpnZPn8ZRoLJq\nPf/9MZ60oio+mBfLwGAPTFKy8NP9pBdX8/H8ERzPLudUXiW+rg6WXLdaR6M1mHCwUzG53u9BZmm1\n1aNNZ2iVo6kVkZsC+AkhsrBEkuwBpJQfYokaXY5FRK4aWFh7rUQI8Tywv/ZWz53ZGAbuwRLNcsay\nCaxsBLcDw8O9+Wr/aTJLqrn54z1cFxvKksnWychVOH90BhM3juxZd3alNZGz+788hKOdiq8Wj8Xf\n3ZJAqZaSPj3cWbY9lauHBONkryKvXMuG43l8s2QsAEWaGp7/5QQvzxmMs4Pl/YwmM7llOkK9Gy/L\nrEFro07nJSJXe20FsKKJ9jhgYGveX6H1RPq51p2juXRAYIeELhXajq+bI0VtzC0K9HQiOsCtzskA\n7EktYd3hbL65eww+rg5Me30r/QI9+OyOUQwM8QTgnc1JzIjpwYx6m775lTW4OKg7bDNdORnczfB2\nseeeKVGMjvThqcv6dfszJl0VlYCj2a0vP3Ego5TdKcX4n1UKIibYAzdHO17flEhOmZaRkT7E55bj\nVa8MyK/H8xqlVBzMKCXc1/XCHqINKI6mmyGE4PFL+/HPWf2wa4OEqkLHEuXv1mTotSl2pxSz8NN9\nPHFZv0YFuDyd7Vl641D2p5fw+Z4MProtlun9erB2v+VUyeHMMqprjPTt0TC/LSm/skODA8pvYjfC\nYDKzL62Er/ad5q/kIlubo9AMX+07zQvrT3LnhF6t6l9QqWN4uDdXN1MYbGSED5cOCMTDyR5HOzVe\nLvb8cjSX+JxyPtmRyoPTezcKeX+2O51e/sqMRqGN6I1mrnpnJ09+f5TdqcU8sOYQ+9JKWh6o0OFk\nllYT5uPCj4ezufvzOApb2Ks5mFFK9FnV72qMJuLSS/hoWwrP/hxPoIcT6w5nozOYmNTHHy8Xe3Ym\nFTUru+Jop6ZnB0WcQCkT0W34ev9p3Bzt+GbJWIQQPP/LCTYcz2VUpI+tTVM4i4em9yE6wI2yagPr\nDuewanc6Vw8JJjrADSEE8Tnl/HI0l3AfFxztVexNK2mUXjD7vb8wmMxE+rnSp4cbSfkaYoI82J9e\nQlapFr3JzA0jQnltYwLqeqfBzWYzqYVV2KtFh9YlUhxNN6CgUsfSP5J49+ZhdZu/I8K9WRuX2cJI\n6/L9wSyW/pHIwGBPBod6Ee7rwsgInwZRk4sRBzsV1w6z7LUM6enF//5I4qNtqSycEEFyvoZ96SVc\nOTiYhLx8dAYTVw4O4saRPRvdR0qJVm9iY3w+p0uq8XK25+VfT5FTruW7e8bh7erItcNC2J5YxJS+\nlnwmlUpFcbWe0io946M7Lu9NcTRdHKPJzKNrj3DV4CDG1ct30RpMqGwYcTKbJUv/SOSxmX2JSy/l\nSGYZq/dmUF5t4JYxYdw2JrzZw2LlWgNIOqyAui0ZHubNqjtG8U1cJt8dzGJavwBevHZQXZpAc6y7\nbxzrDmWzN7WEYWFe3DE+kuIqPQUVOkK8nesiSjeNCuO25Xup0Nbw/64bjFqtJim/kh6ezrg7ddy/\nr+JoujBSSv697jiVOiNPXxFT116hM/DaxgSemNXPZrYdOF0KwNVDghuEVuPSS1i+M40r3t7JNUOD\nuWlkWIOUiWNZ5cxbvhe1SvDdPeOI9Ou4DUtbcv2Inlw/ovGspTkc7dTcODKMG0f+nWjs7erQaD9m\nWE8vpvYNID6nEo1Gg6enJ1q9iZIqfbvZ3hqUzeAuzN60EnalFPHx/BEN9IhSC6tQCcHsYbYrR+nj\n6kBZtYFPd6U3aB8R4cMH82J6MVKfAAAgAElEQVRZc9cYpIRr39/FvasPcCKngp1JRdy/5iCPX9qX\n64aHcNOy3ZwurrbNA3RxTuVVcONHuxn10maOZpfx5GX9cHe3hLhHRvqgqTF2qAKnMqPpgpjNkv3p\nJbyy4RQ3jujZaM/jvS3JXDPUNhpJZ4jyd2Pt3WNZ+Ol+kgo0vHTtwAaHB2OCPXh+9kAWT+rFF3sy\nuOKdHYT5uHDFoCDmjQnHZJaUaw1c895O7p4cxQ0jenbpEqQdzRd7MgjwcOKpy/vTP8i9QXF1Nwc7\nTGbZoUtr0dZygLZkxIgRMi4uztZm2AxNjZE3NiXww6Fs7NUq5gwL4bFL+9bVBAbLcqrff35jy2NT\nCPbqmDyWs9EZTHURjWJNDTcu28OsAYE8dmnfZsfklmvxd3NscMjQZJb8lVLE0t8TSSuq4r1bhjfY\nh1JoniWfH2BEhCUbvD655VpuWraHar2R/U/PuOD3EUIckFKOaKmfMqPpIuRX6Ljl4z30C/Jg7d1j\n6V0bCj2bPakleDrbW00241yYzZJnf47n8z0ZPHlZPxZPisLXzZFVd4ziynd2MirSp9ks8qZqrqhV\ngom9/ZkQ7ceafZksWhXHh/NiL6pM9BqjCYda59uWdJJrhgZz35cHuWZoCP7ujqw/lsMvR3LJK9cx\nrKcXT13e31omN4niaLoABpOZ+788yCUxPXhyVvP5Syaz5NWNp3hweu8GZyc6ip+P5rA1sZAv7hzN\nnZ/F0TfQg8l9/An2cub5awbyyNrD7H/6kjbnXwkhuGV0GA52Ku5dfZBfHphAxHluEusMJvanl9DD\nw4keHk54ONl12nywZdtTeGXDKTyc7dEZTNw5IZLHL23dBn9suDeOdmpO5lbw6m857EkrJtrfjVG9\nfHhsZsNZcEegOJouwJp9p9GbJI/O6Nvsh+JARikfbE3BLOGGNkQvLhSt3sSfpwrYfCqfP08VsGBs\nBOOi/Xh0Zh/u//IgH82LZVy0H5cNDOSlX0/y0q8nG0TI2sLc2FCOZ5fz7M/xfLpwVJvGSin5+Wgu\na/aeJq9Ch95opqBSh6ezAzNiArhsYBAjIrxxcegcH4n3tybz5d7TbH1sKmq1ILlAw3/WHefDbalc\nNjCQd28Zfs7x/u6OjIz0Yf6KfdwwIpR/TO/DnOEhtnOqZ2QbusIrNjZWXmzUGExy3Mub5Z8n85u8\nHp9dLu9cuU8Of26TfPnXk7JSZ+hQ+5Z8HievfmeH/Hh7ikwpqGxw7at9GTL6X+vlKxtOSqPJLNMK\nNXLgM7/J9Udzzvv9Sqtq5OD/2yjnvL9LphVqWj3u3T+T5Mw3t8mXfz0pk/ItdprNZpmUXyFf+vWE\nnPHmVnn/lwfP26725PPd6XL8K5tlZklVg3aD0SRLq2rk+Fc2yzV7M1q8j1ZvlEcyS6XZbLaWqRKI\nk6347Crh7U5OapEGo9nM1CYE2NOKqpi3fC99A93Z/s+pPHlZP9w6uFi30SyZMzyURRN70eusfJwb\nRvTkh3vH8+fJAh766hD+7o58evtI/vntUdYdym6zLhGAl4sDO56YioeTHT8ebl3117SiKr4/mMXt\n4yN48rJ+dWdNhBBEB7jz1GX9ef/W4exLK26zPdbghfUnePeW4Y0ONNqpVXg62+Pt4kCZ1tDifZzs\n1QwO9eoUS0PF0XRyEvIqmzxBG5dewrXv7+LuSb14/NJ+NlMDuGpIMB/vSEVvbHwmQwjBwBBPPlkw\nguwyLQtX7qenjwsrbh/J//5I5P4vD6EzmNr8nhqdkUOZZeeUCdlyqoCnvj/Kbcv3cvOyPQwL8z7n\nJnKknxvlWgNl1R17kO1sKnUWB2LXzB6bySwxmSVHMsvOy1HbitYqVc4SQiTUqko+2cT1cCHE5lqV\nyq1CiNDa9qlCiMP1XjohxOzaayuFEGn1rg1t30frHvTwcCK/QofZ/PcvVYXOwMKV+3liVj/utnGZ\nzlkDAnF1sGPV7vRm+/T0cWHlwlH4uzlyzbu7CPNxYf2DE6kxmrht+V4yS1p/KM9oMvPU98e4dlhI\nXQW5s9EbzSxaFUewpzO3jQnnycv6ceeESELOEe5XqwQRvq4ca0MxKmuQVlSFj4sDMUEeTV63U6tY\ns3gMB09bCmGdoarGyA0f7mbKa1s4VHsquzPRoqMRQqiB97CoUcYANwshzt7Nex2LgNxg4DngZQAp\n5RYp5VAp5VBgGpZ6wpvqjXv8zHUp5eELf5zux4hwbwLcHXl5w8m6tjV7TzMszJubR9le58rBTsVL\ncwbx7pZkssu0zfbzdLbn3VuGMbmPPwtX7kcI+GBeLMPDvbn87R28uSmhxW9ok1ny+LdHKavWnzO9\nwiwlZilZOCGSmQMCmT0spE4T6VzcOjqMVzacOq9ZVnuhVgk0NUb+PFXQbB9PZ3tiw7154/dEfj5i\nWT6+vikBZwc1D0zrzV2rDlCha3lp1ZG0ZkYzCkiWUqZKKfXAV1iUKesTA2yu/XlLE9cB5gIbpJTK\nmfI2YKdW8f6tsfx6LI/7vzzIE98e5f2tKTxcKyBmLeJzypm/Yh87k1ouoBUb7s2cYaEs+fwABZW6\nZvsJIXhpziD83R15648k7NUqnrqsPz/fP4FNJ/J5cf3JZp2N2Sx58rujpBZqWHXn6HOWOMiv0OGg\nVmGvbtvexC2jwwn0cOLf62yn6T0g2JM3bxjKw2sP89T3Rxu8nv/lRN3M9vZxkYwI9+alX0+ybHsK\n3x7I4oXZAzFLSY3R1ORS1pa0xtE0pzZZnyPAdbU/Xwu4CyHOzkG/CVhzVtuLtcutpUKIJmsHCCEW\nCyHihBBxhYWFrTC3+xHo6cRP949nUIgnUQGu/HjfeIZZUduorFrP3Z8fwEEteOan4636hn/6iv7E\nBHkwf/k+qvXGZvupVYLHZvbhu4NZdR+aCD9XVi8azY6kIl76tbGzKays4el1x0nIr2TVnaPxdD53\n1vG6QzkM7enV4Nh9a1CrBEtvGsqfpwo4bsMl1CUxPXj7pmH07eFe97JXq9ia8PcsZ1SkD09d3p/p\n/QP47XgeBpMZPzdHvj+YzX+uiMHPrXOV4miNo2mNquRjwGQhxCFgMpAN1P221epwDwI21hvzFNAP\nGAn4AE809eZSymVSyhFSyhH+/hfPidCz8XVz5O7JUSyeFHXeh9Vag9kseXTtESb38ef9W2NxdbRj\nY3xei+PUKsHLcwYR6u3Mw18fxmRufhk0MNgTg0kSn1NR1+br5sjqu0azLbGQlzecqnM2Px7OZuKr\nf5JVWs3nd7TsZIwmM8u2p/DcNecnsOHhZM+80WE898sJXt+YwH9/PM6iz/Zz2/K9nMytaPkG7cTU\nfgHcPj6y7jW5jz8B7k6NJI23JhRyx4RIDCZJSqGG+JzyTlnsrDWhiuZUKOuQUuYAcwCEEG7AdVLK\n+l8JNwA/SCkN9cbk1v5YI4T4FIuzUrAhJrNk0Wf7KdcaeO/W4TjYqZgZ04PHvjnC6j2nuWpoMPNG\nhzUbLlWpBEtvHMpty/dx6yd7mD82gun9AxrNLFQqwX1To7j+o78I83FhZkwgC8ZF4O/uyJd3jeGW\nj/egN5rxdnFgxa403rtlONP7t04fuqCyBpUQ9A10b7lzM8wbE47RbNnnCfZyJjbcm5+P5PDHifxW\n7fVYA7MEedb3u5SSkio9L/96isWTevHHyXwGBHta9YvofGmNo9kP9BZCRGKZqdwE3FK/gxDCDyiR\nUpqxzFTO1nG6uba9/pggaVGzFMBswHYLYwXAkvVdrjXw9d1j646o3z+tN1cPCWFPWjGvbUygf6A7\nIyKa/8Z0d7Ln67vHcNsn+3jmp3hmNiMgv3hSFFcODia5QMN3B7O48p0dvDp3COOjfPnyrjE8+d1R\nqmqMrL17bJucxi9Hcxga5tW2Bz+LAA8n/nnWZvOm+PwGEiYdjUpAWXXDDV4hBG/eMJTCSh2HMss4\nnFnG2zcNs5GF56ZFRyOlNAoh7sey7FEDK6SU8UKI57CcCvwJi4rly0IICWynnpicECICy4xo21m3\nXi2E8MeyNDsMLLngp1E4b7YkFLDyr3R+un98ozyYMF8Xgr2ceHNTYoO6N82xO6WYpIJKXps75Jz9\ngr2cCfZyZlIff749kMU/vz3CgGBPVtw+kk8WjDyv59DojFaRebVTCyp0ze89WZte/m5kl2m57K0d\nTO8XQEJ+JU72agoqdGgNJjKKq/n9kUkEuHd8Mm1raK1S5a9YZG/rt/233s/fAt82MzadxpvHSCmn\ntcVQBeuRUqjhoTWHmjyNeobMUi1FmpoWK95paox8tC2Vm0aFcUkzs5mmmBsbyhWDgpj82ha2JRY2\n0IhuC6HeLiTma85r7LkI9HQiMb+y3e/bWiL9XNn++FR2pRRx6HQZoyJ8KKqqoV+gO072avoHuRPg\n7kRVjRFne3WjvRxb0zkyyBRsgpSS7DItj6w9wo0je57z5Gx+hQ5nezWZJVpigptfQmw4lkuZ1nBe\niZ2WcyDRLN+Zdt6Oxs/dgfTiKgoqde367e6oVnGO/e0OwdvVgSsHB3Pl4IZFzf48lc/KXek89/MJ\n0our6BvowSfzR3SqIvBKCsJFyp7UYgY/u4lpb2xjZLg3T1527vokoyN9mDM8hMe/PXLOcHe13oSd\nSpxXrd/SKj3LdqQy+gKiJuOj/XB2UDNz6Xb+ve4Yx7LKL/io/qm8ClbsSuceG5/Cboq/kot4+Osj\n9AvyYGyUL29cP5SqGiPbEzvXURDF0Vyk7EouYnIff049N4t/XxnTYv0aIQQPz+iDr5sjd362n28P\nZDXZb196yXmfWP50VxoRvq7cNzX6vMaDpWj3D/eOZ8XtI3G0UzN/xV5e2/j3qeM9qcV8uiuNIk0N\npa0s0L0/vZQ+PdwaFFHvDNQYTXywLYUlk6N4ZEYfnrlqAFcMDsLJXoWqk32ylaXTRco1Q4O56p1d\nZJdp6enTus1TLxcHlt0Wyxd7MnhvSzLZpVoeOuuEsq+rw3kdf9+SUMCKXel8s2Rsm8c2xfAwb4aH\neXPXxF7ctnwv5VoDz149gJc3nKJSa+DF9ScxmiUDQzxYdcfoBvWIDSYz9mpVnXPKKq1usgKgrfl8\ndwYVOiNzhjfcAo30c0NTY7s0iqZQHM1FSnSAO4smRjL9jW3cPy2aB6e3LqXByV7Noom9uHJwMHPe\n34WmxsCdE3rV6RCF+biQWlTV7Pjkgkq8XRzwcXVAZzBzOLOMD7alcCKnnNevH9zu51QCPZ34avEY\n7loVx5IvDpJRXMUP944n0s+VSp2By97awanciga1iN/5M5nSKj2HM8sI8nRiS0IBy+a3WBa3QzGb\nJV/uO80/L+3bqGxraZUeD6fO9dHuXNYodCiPzuzL5YOCuP7D3RRpanj80r6tFhUL9HTiy7vGsOSL\nAxzPrmDN4jGAJVN7W2IhJrMl56bGYCanXMve1BI+3pFKtd6EzmBCYsmyDvd14ZZRYXxw63Crlbrw\ndbMcBHzulxNcHxtKhK9lBufuZI9KCBzr5U2ZzZLPd6fj7+7IsJ7eODuo2fXktE4VNq7WG7nynZ0U\na/RM7tO4VEa51tDpcp0UFQQFcsq0PLr2CEkFGoaHeTF/bATjonxbFSJNKdRw5ds72fPUdDxd7Ekr\nquLqd3cS4uVMQn4lKiEIcHdkcKgnt44OZ2yULyazRFNjxMPJvlXncqzJ0z8c43h2OTMHBDIszIuU\nAg2rdmew4aGJDRQZOhPfHcjii70ZfDx/RJM5Td8dyOJ/mxP58b4JVpeoUVQQFFpNsJczqxeNZl96\nCTuTipi3fC+/PDCh2XovZyip0vPGpgQc7VV1DiPSz5XlC0aSX6FjfLQfHk52jT6w9mo6VGD+XPz7\nihg2xudx8HQpL/16kuoaE8/PHthpnczOpCL+8+NxHpnRp9nEyTnDQ/j1WC4/Hs5m4fjIDrawaRRH\nowBY8o9UQvDTkRwm9vZrJK16NnHpJTz01WFG9/Jh4z8m4ezwt+PojEl9zeHsoGb2sBCbqnq2hRO5\n5UzrF9BIr6k+QgiG9vTiVK7tDhiejeJoFOr4eEcqA0M8ePfm4c0um3LKtLyy4RR/pRTz5GX9mBsb\n2sFWXtyohMBklpjNstH/kcks+eNkPp/vzuBoVhn3TDn/YwLtjbJHo1DH/vQSnvzuKJ7O9kzpG8DN\no8LqTpfqDCaWbU/lkx2W9IIHpkW3euNY4fyp1BnYcCyPlCIN80aHo1IJpr6+lXdvHsbMAYEAFGlq\n+O14HhnFVXxzIIvHL+3L6EgfovybFhlsT5Q9GoU2MzLCh/UPTmRrQiHfHshiw/F9LBgbTpCXM0//\ncIzeAW6su298I7UDBetQqTMwb/k+3BzVeLk48NT3x/h4fiwms2wgd+zt4sDhzDL+PFXA+gcnnrM2\nsq1QHI1CA5zs1cwaGMiMmB58eyCTdYdySMyvZP7YiEaH8xSsyxPfHSXK35XX5w7BYDYz/Y1tHDxd\nhrO9mhO5FQwI9iAxX8MNH+2mXGvg8kGBndLJgLJ0UlDolGj1JoY//zt/PTkN79oQ9RubEqjWmzhd\nUo3RZGZwqBcFlTpqjGZemD0QZ3t1h2s4KUsnBYUuzLHsciL8XOucDFhKcHg5OzAh2o+3NyeRVlSF\n3mjmkwUjO42Ub3N0busUFC5SUgo19D7riIGzvZoNx3N58dpBHPjPDBtZdn50zlNJ3ZTCyhrmfbKX\nj7alNGjvbMfFFWzPiZyKRiVMH5vZlwXjIlj46T6SbFiE63ywqlJl7TVTPTXKn+q1Rwoh9gohkoQQ\nXwshrHtWuhPw+4l8ijQ1/L/fTqGpsZSF3JFUSMx/f+O25XttKlym0Lk4klXG4NCGJ7NVKsHNo8KY\nNyac5TvTbGTZ+WFVpcpatPXUKK+u1/7/gKVSyt5AKXDnBTxHl2BfWjFqlaCXvxuutSdp39mcxK2j\nwynW6Fm8Ko70c2Q+K1w8jIzwYcXOtCYF+W4fF8H6o7ltkhK2NR2pVFlHrfLBNP6uM/wZFiWEbs2D\n03szPMybD+cNRwiB3mhmX3opSyb34qN5sQR6OnHVOzv57XjLOkoK3ZuHZ/QhxNuZ6W9s49G1R9id\nUlwnuBfg4cSSKVEsXGmRxukKdIRSpVOt0uQeIcQZZ+ILlEkpz5SVb+qeQPdSquzl78bzswcSHWBZ\nexdqalCrBPZ2gp6+Lrw6dwg3juzJtk5WhlGh43FztOOF2YPY9PAkevm78vQPx5j+5ja+PZCF0WTm\n3ilRhPm48NORnJZv1gnoCKXKsNo4+y3A/4QQUa28p6WxGytVbksowNvFHj+3v2udhHo7k1zQtTb6\nFKxHkKcz902NZvOjk3nmqhhW7U5n4cr9VOlNzIjpwe6UlrXROwOtcTStUqqUUs6RUg4Dnq5tKz9z\nrfbPVGArMAwoAryEEHbN3fNiIK2oihpDw4jTpQMDicsoxWBSIlEKfyOEYErfAL67Zxy+rg6Me3kz\nL/16Emf7rnFCxapKlUIIb6BaSllT22c88KqUUgohtgBzsez5LAB+bKdn6jJU602MiPBu0OZop8ZB\nraJIU9Mp69Qq2BZ7tYqlNw4lq1SLnVrQoxNV/jsXLc5oavdRzihVngTWnlGqFEKciSJNARKEEIlA\nD+DF2vb+QJwQ4giWTeJXpJQnaq89ATwihEjGsmezvJ2eqcuwJ7WYs0+M26stDV0oM0ShgxFC0NPH\nhSBPZ/Qm8wXLyXQEVlWqlFL+BQxq5p6pWCJaFy2ujnaNkuDcnewJ8XKmoLKmQYaugsIZaowm1sZl\nsXpPBon5lUzs7c/bNw3D04ba4C2hnAy2ITUGMyoheH1jAo+uPcznuzPQGUwUampws1KhboWujZSS\nm5ftYf3RHP51eX8OPzOTEG9nrn1/F9V622mDt4TiaGzInRMjyavQkVygoVij57O/0hj14h8EejgR\n5d92pUeF7s+RrHLyynWsXjSGSX388XCyZ2SEN4WamkaBhc6E8rVpQ24Y0bOBRrXRZCatqIowX5cO\nT/c/XwoqdKQUVhEd4NaptJ67KxnFVfQP8migLJqQp2FubGiDTO/OhjKj6UTYqVX07uGOo13nUAg4\nFwdPl7L090SmvbGNx745wqLP9tvapIuC/kEenMytaNA2Z3gIPxzK7tSbwoqjUWgzyQUaFqzYx8b4\nPJ6Y1ZePboultLprHIXv6vTyc6VcayC7TFvX1jvADb3RTHErtcRtwUXvaA6eLuWbuEy2JhTY2pRO\nT1m1ntc3JvDsz/GMivDht39M4raxETjZqynXGjr1N2p3wU6t4qohwXy173RdmxCCfoHu7EruvKeE\nL2pHczy7nFs+3sOq3Rk8/PVhjmSW2dqkTstj3xxh5It/cDS7nIm9/Xj9+iF110K9nXFztGOrkqPV\nIcwZHtoo8faBab158/fETltq5KJ2NN8dzGJUpC8/3T8ef3dH1h3OtrVJnZIKnYEfDmWzetEYXp87\nmMWTohpsPDrZq+nTw41iTeeduncnwnxcyK/QNZhBTunrTy8/V97anGRDy5rnonY02xMLGR/lS2Fl\nDV4uDopOUTO4Otjh4qAm2MuJAI/GR95zyrQcyy6nf5B7E6MV2psAd0d6eDixZt/fRRWEEPzr8v6s\n3Z95jpG2o1uGt8urDWxJKODSAYENpFozS6r56UgOhZU1zBzQgycv68/rGxN4bWMCA4I9WDK5eZnR\nixm1SjAw2JMjmeWEers0uFauNfDU98cY3cuXAcHn1upWaB9UKsFbNw3j5o/34GCnQkrJ3rQSNp/M\nb1Ev3VZ0S0fzr3XH2JtawncHs/hwXizO9mp+PZ7L87+cYGSED6HeLixYsY99/7qEjQ9PoqBSh7eL\nA/adVNi9MzAq0oc/TuZzxeAgwHJCVQjBip1paA0m3rllmI0tvLiICfbghdkD+f5gFq6OdoT7uvDT\n/RMI9e6caSvdUtfp4+2prPwrHT93RwxGM3qTGZ3BxIvXDsLZXs3rGxOoMZn5/p5xDQ4+KTRPkaaG\nq9/ZSaCnE7383TiWVY6PqwNpRVV8sWhUXTEvhYuL1uo6dUtHI6Xk+V9OsjE+jysHBzEq0odxUX6k\nFGr4x9eHuWZIMAsnRCr5RG2kSFNDXHopR7LK8HK2x2iWzBsd3qmT+RSsy0UtICeE4D9X9gdga0Ih\nBpPk8W+P4minYlSkD/dOjVZmMueBn5sjswYGMmtgoK1NUehidEtHA387m493pFJabWDVHaM67UaZ\ngkJ3p9s6GrA4m8WTomxthoLCRY9VBeSEEEOFELuFEPG1126sN2alECKtnrjc0PZ7LAUFhc6EtQXk\nqoH5UsoBwCwsKghe9cY9Xk9c7vAFPouCgkInxaoCclLKRCllUu3POUAB0L00UxQUFFqkIwTkABBC\njAIcgPoK9y/WLqmWCiGUqkkKF4TeaKZIU2NrMxSaoDWbwa0VkHtXCHE7sJ2GAnIIIYKAz4EFtZIs\nYJFlycPifJZhUUV4rtGbC7EYWAwQFhbWCnMVLib2pZXw+sYEXBzVFGv0JOZXcvv4CJ64tB8q5QhD\np8HqAnJCCA9gPfBvKeWeemNypYUa4FOaUUTozkqVChfO1/szGRzqSZCnEzNjerD18SnsSCxixa40\nW5umUA9rC8g5AD9g2Sj+5qwxQVLKXGEpjjsbOH6hD6Nw8VFWrWdKX3+uGhJc1/b87IEsXhXHoolK\nkmxnwdoCcjcAk4DbmwhjrxZCHAOOAX7AC+31UAoXB8ezyzmeU06kX0PFiBO5FcSGezczSsEWWFtA\n7gvgi2buOa1Nlioo1GIyS5756Tgb4/O5eWRPevdwa3Bt5a40nrqsvw0tVDibbn0yWKF7smp3Osey\nK/jj4cmNEjp/PJyNm6Md0/sH2MY4hSZRCrB0A3YlF/Hw14fZFJ/XcuduwF8pxdw2pums8U3x+dwy\nOqzL6GJdLCiOpotTXm3gni8OEB3gxrM/n2DFzu4fbYn0c2V/WkmT13RGE26OStmKzobiaLo4JdV6\n1CrBPZOjWL1oNP/7I5H8Cp2tzTpv9EYzBzJKMJjMVOqalnBZPKkXG47nkpRf2ejahGg/Xt+UoBzc\n62QojqaLY68WCCFQqQQRfq4MCvUkLr3U1madN8/+HM+dn8XR/z+/MfjZTTz1/bFGffzcHHl8Vj9u\n/3R/AyE1gBkxPSjXGjiRU9FonILtUDaDuzjJBRoC6mlex4Z5cziztK62b1dCbzSzMT6flQtHEe7j\nQkFlDTd/vIdL+udzSUyPBn1vGxNOhdbATct2c9PIMEZH+nDodBkfbEvh7km9mNjbz0ZPodAUiqPp\n4jioVeSUaamqMeLqaEdivoaJfbrmh+x0SRVGs5khoZ4IIfB2deDDebHcuXI/vm6W4vHf3TsOj1pZ\nnPumRtMv0J0tCQX864djhPm4snLhSAaHerXwTgodjeJoujhjo3wZGubNDR/t5srBwexNK+alOYNs\nbdZ5kV9Rg4eTfYOI0ahIH1beYclOufvzA2SXavEI+nuzd3r/Hkzv36PRvRQ6F8oeTRdHCMHyBSPw\ncLLn7c1JrFk8Bp96KpJdCYPJjEs9Ha4zxIZ7MzDEgwqdAd8u+mwXO8qMphtgr1bxxaLRaA2mLq3s\nMCrSh3KtgdV7M7h1dHiDa/YqFUaTuYEgoELXQZnRdBPUKtGlnQyAi4MdS28cyv/+SKJCZ2hw7URu\nBZ7O9jjbdy1Hk5BXyXtbklm5K63JUP3FguJoFDoVY3r54u5kR2JewzMyueU6wnxcsOtCaqLJBZXM\neX8XBzNKeXVjAimFGlubZDO6zv+awkXD2F6+fH2WWH2UvyvJBV3rg7r5ZAF2ahWvzh3MzJgePLDm\nMJ/vTmf90VzMZklygYb//ZHINe/t4q/kIluba1UUR6PQ6Zjcx5+DpxseOiyu0hPs1Tl1pZvjo+2p\nrLh9JL5ujiy9cSjjo3w5dLqMtzcnMWPpNq58Zwd/nirgxhE9eWTtEYwmc8s37aJ07UW9Qrck0NOJ\nkio9Usq6ULeXsz3FVdaFoyAAABE8SURBVHobW9Z6tHrLxvw7fyaxcuEohBD8+0qLeEiRpoZtCYVE\nBbjh5WyPr5sDz/0ST0FlTZdzpq1FmdEodDqOZJbR08cZk0nW5W3lVei6RNi+xmhiZ1IR133wF316\nuPN/Vw1o1MfPzZHrYkMZ2tOLCD9X7FQqXB3s+Gx3erfdMFZmNAqdDju1ihM5lby26RQFlXquHxHC\nA2sOcX1sqK1Na5F7vzjI4cwy5o0J5x+X9G5VuQpnBzWr7xrNg2sO0TvAnbld4DnbilWVKmuvLRBC\nJNW+FtRrjxVCHKu959tCKSCiUMv1saF4udgzLtqPCD8XPtmeBhIqdUbM5s79jZ9TrmPh+AgentGn\nTTVx+gV6cOvocLYmFNS1FWlquG/1QT7ZkWoNUzsUqypVCiF8gGeA0VhUDp4RQpwp5voBFhmV3rWv\nWRf8NArdAju1iptHhfHLkVwemt6HW0aH4eliz4GMUrYlFtravHPyf1fFsPSPJLR6U5vGVeuNrNl3\nml7+lrKkh06XcuvHe3FztOPN3xO7fNkLqypVApcCv0spS6SUpcDvwKxanScPKeVuaVmUrsKihKCg\nAEBptZ6K2no0l8QEsu3xqf+/vTOPjqrK8/jnV9k3KhtZSEgkBMImmxGRZlVEZWSgnUFRVGxEe+y2\n9aDtOXbbLR60p4869kw7LrQLI7Zt27gSF0REQQTMIhgSEkISQkNIyGIEQiIJkDt/1CWphKxQlVq8\nn3PeqZvfXX/vpX713n3v3S/zxw/i0wL3XkXQ18eCNciPAN/eT38WVh5nwXPbGBoTyr2zUnk0Yw93\nvpbD3Ivjefi6kfj5WDh5qm+By91wtlJlV3UTdLq7NgGbgJyI5IhITk2Ne/+aGRzHokuT2F/TwP1r\nc2k6bfuShQb4cvzk6R5qupb//byYGy8d3GvxumM/nOLO13JYdGkS/3PDeB7/uJCtxTV8fN80ZqYN\nZM6fvuTKkTEkRgQ7eeTOpTeBprdKlTNEZBcwgzalyq7q9qZNm9EIyP0oGZNgZc3SSWTkVtDQZAs0\nE5IiyNz/HQ1N7htsfC1CfYfXJ7piRcYeZjz1BUopcsuP8v6ucj7cXcHq2y8lJiyQL/fVYA3yY0Un\nd648DWcrVXZVt1ynu2zTYAjx98UCtGgV5XGDwxmbGM4rbrwu8mMLxpDxbQXPfVHCmR4mrofHhrJ8\n9nDumDqE/PKjPPRePgG+PiRH2XSq7pyeQsrAEBau2s4JNw6uvaE3gaZVqVIrTy4CMuwLiEi0iJxt\nq1WpEpvo3BwRidCTwHOADUqpSqBeRCbru023Aesc4I/Bi7AG+5EUFczdr+9stc0bF0/2gc4XJncH\n4q1BxA4IJCLYH58eLp8WX5bMkikXsXRqCuvumca6X05hckokmwqrAAj08+HZmydy5NhJDtU19sfw\nnYZTlSqVUnXAY9iCVTawUtsA7gZeBkqAUmC9o5wyeA8LLxmM/TNsmWV1bnkHxv7s5aFrR/DUhr3s\n78NLlKGBvoxJCCchPIj/eP0bcg7UoZRiR+l3BPr5MCwmtOdG3BinKlXqvNW0neHY23OAMX0ZrOHH\nR2igb7vH8m9MH8w735RTdfwksQMCXTiyNvYesd01GpsYziPXjeLKkbFMSY3ms8Iq7hrYtwCRGhvG\nsJhQlqzOIio0gMbmM1w/McGj3lrvDPNksMGtyT5Qx8SktjWAJyRFEOLvw/eNzW4TaBqaThM7IJBr\nRsexcNUOfCxCsL8PD85J67FuS0sLFktbEBkVH0Z1fTPZv5tNVlkd/r4W0pMjnTn8fsEEGoNbYw3y\no7Cy/do0IsKa7Qf44/VjXTSq9oxLDOdo4ylGxYfx+rLLyD10lEWTBhPs3/PXq/ZEMzF2ATMlOpQT\nTadobD7DzDTvkfX17PMxg9dz/1XD+aqkljcyD7ba/rDgYt7fVUH+4WMuHFkbvj4WVswbxc9ezeFQ\nXSNLpw7pVZABCA9s/xXMOlBHRLC/162NbAKNwa0JD/bnxdsu4dnPi1mRkQ/A3LHx3Dd7GC9sKXXx\n6Nq4fmIilw+Noqy28wngZWuyueeNnXxWYLujlH/4GI9/VMA737Z/0jktNowgfx9Wbzvg7CH3KybQ\nGNye0YOsPDJvNK9/fZC3cw7RfLqFP39WzKj4Aa4eWjvGJlrZWlzLm1kHKa05QdGReraV1LLz4Pdk\nldVhDfRjRcYebvjLDm55JZMv99XwSX5luzYiQvz5+fQUMvd/5yIvnIOZozF4BNeMiWPK0ChONJ1u\nfc5k2bQhLh5Ve5ZcfhEVR38gI7eCJz7ZS5CfD9Zgf441NnPPFancNX0oxxpPsXlfNZenRIHAdc98\nxdf7v2NySlRrOx/lHWGeByqNdocJNAaPYdqwaFZ+WMDoQVaeXzyRAF/3UkSICPHnyX8f120Za7Af\n88e3vdY3Ky2GTYVV7QKNRWDnwe/5KK+SID8fHl8whqjQgM6a8xjMpZPBY7hr+lCKHr+WD341lVkj\nvOOOzPKrhvPWN+XklbdNbF+cYKW0uoG5F8cTGeLP0jU5vX5/yl0xgcbgUfh5+INrHYmzBvLrOWk8\n/H5e66Jeo+IH8Mi8UdyQPpiV88eQEB7I05/uc/FILwzvOmoGg5tSf/IUj31YwE+f38ayNdn85t3d\n/GVLKafOtHDzpCTOtCje2WlbOWVKajS7Dh0FbMKAy2cPZ923h9ldftSVLlwQJtAYDP1ARm4F20pq\nuf+q4cwfn8CwmDBe2rqfrLI6LBZh5fwx/HH9XiqP/YA1yI+6E22KD8Niw3hgThq3rc5im4fqP5lA\nYzA4iNoTTTyzqZhHM/bwyLp8GpvblnYYFhNGXUMzU1OjmTduECkDbUtBpMWFAXBJcgQ3T0ri9+/v\nAWBG2sB2t7hvmZzM/HGDyHOThxT7igk0BsMFUnX8JDtKv2Ppq9nsq6onKsSfz/dWk1XWtpzFwbpG\n0i+KQESoa2hm5YcFLJuWQrTd3aSfz0hh75HjPLA2lxFxYRRV1VNS3fb6RVcrxnkCJtAYDBdAYeVx\npj7xOSsy8pmYFMGfF01gwYQEak80MSKu7YHChqbT1NQ3oZTiDx8VMi7RilKKW17O5IG1uWwuqiYs\n0I/1902jqOo4q7aUcuvkZCqOnmyVyw3y86Gu0XNE9OwxgcZguACsQX5YRJg9MpaQAB9++24ed6zJ\n5ob0wcRZ216WXDAhgarjTcz+0xY+yK3g47wjrNpSysj4AfhYYOUHBQCEBfrx3M0Tycit4Lfv5TM1\nNZqnPi1ie0ktYxPDeSPzIH/L/Ker3D1vxJOU8dLT01VOTo6rh2EwtOOLomq+Kq5FgPBgP2IGBHLd\n2PhzXqxsaDrNktVZ+PoIK/91NF+X1ZEcGcxLW8uIswbyXwvbHvY79sMpbn0lk+bTLdQ1NOPnY2HL\ngzPZXFTDf64v5PMHZvavk10gIt8opdJ7KmeeDDYYLpBZaTHM6sWSDiEBvhz6vpE37pzM0IGhpMaE\nsuD57ZRWn2DD8untylqD/HjzrslsKqxmytAoFr+cydaSWl7aup95Ywc5yxWn4SilyiQR+UJEdmm1\nyrnavlhEvrXbWkRkvM7brNs8m+cdj3oaDN0wPDaM9XmVKKXYsKeKgorjPLt4QqdyKsH+vswbN4io\n0ACSo4J58pMiTp1p4Z4rUl0w8gujx0snrVS5D7gKm3pBNnCTUqrArsyLwC6l1AtaxfJjpdRFHdq5\nGFinlErRf28Gfq2X9OwV5tLJ4OmU1TawbE021fVN+PlY+O8bxzNjeM8yQrvLj/LuzsPcMXUIgyPd\nR+PJkZdOrUqVuuGzSpUFdmUUcHaK3Urn0ik3AX/vRX8Gg9cyJDqEjctnUF3fRGSIP/69VLQcm2iT\nmvFUHKVU+Shwi4iUY1vE/FedtHMj5waa/9OXTb+XLhTRjVKlwduwWIQ4a2Cvg8zpMy1UHz/p5FE5\nl96c0fRGVfIm4FWl1NMicjnwVxEZo5RN+UtELgMalVL5dnUWK6UOi0gY8A5wKzYN7vYdKfUi8CLY\nLp16MV6DweNRSvG3zIN8nFdJ9oE6LCJMGhLJ0p8MwWIRpqZG96gb5U44RKkSuANYC6CU2gEEAtF2\n+YvocDajlDqsP+uBN7BdohkMBuDTgiqe2VTMoklJfHTvNDY/OJOxiVZ+/VYuD76V2/oCpqfgEKVK\n4CBwJYCIjMQWaGr03xZgIfDm2cIi4isi0TrtB1wH5GMwGABIjgqm+UwL01KjGR4bRrw1iAevHkHO\n72ZzSXIE9Sc9SyLXUUqVDwB3ikgutjOX21Xb7azpQPnZyWRNALBBRHYD3wKHgZcc4pHB4AWMiBvA\nFWkxrN7WXme85kQTX+6rYVZaz3eq3AnzZLDB4KYUV9Xzby9s55XbL+WH5jP8s66RrftqaFHw8pIe\n7yj3C+bJYIPBwxkWG8a9Vw7j3r/vIiE8iKSoYEYPsnL9xI43fd0fE2gMBjdm2bQUlk1LcfUwLhjz\n9rbBYHA6JtAYDAanYwKNwWBwOibQGAwGp2MCjcFgcDom0BgMBqdjAo3BYHA6JtAYDAanYwKNwWBw\nOh71rpOI1AD9pTURDXim/ui5eJMv4F3+eLovyUqpHt/w9KhA05+ISE5vXhbzBLzJF/Auf7zJl+4w\nl04Gg8HpmEBjMBicjgk0XfOiqwfgQLzJF/Auf7zJly4xczQGg8HpmDMag8HgdEygMRgMTsfrAo2I\nLBSRPVrnO71D3m+0fniRiFxtZ+9UW1wrP2SKSLGI/EOrQCAiAfrvEp1/0fn20UffHhWRw3Z65XPd\nwbf+whH70MHjOSAiefpY5GhbpIhs1Pt1o4hEaLuIyDN67LtFZKJdO0t0+WIRWWJnv0S3X6LrSnd9\nuDVKKa/agJFAGrAZSLezjwJysSkwDAFKAR+9lQIpgL8uM0rXWQss0ulVwN06/QtglU4vAv5xvn30\n0bdHsemVd7S7zLd+PK4O2YcOHtMBILqD7UngIZ1+CHhCp+cC67EJMk4GMrU9EtivPyN0OkLnZQGX\n6zrrgWu768OdN687o1FKFSqlijrJmg+8qZRqUkqVASXYROtatcWVUs3Y9Kfm61+PK4C3df01wAK7\nttbo9NvAlbp8n/pwoNuu9K2/cPY+dBT2+6/jfn1N2fgaCBeReOBqYKNSqk4p9T2wEbhG5w1QSu1Q\ntojyGp0fI/s+3BavCzTd0JWGeFf2KOCosula2dvbtaXzj+nyfe3jfLhHn3qvtjtldqVv/YWr++8M\nBXwqIt+IyF3aFquUqgTQnzHa3tdjlKDTHe3d9eG2eKQKgoh8BsR1kvWwUmpdV9U6sSk6D7aqm/Ld\ntdXXPs6hO9+AF4DHdN3HgKeBpefRryN96y9c3X9n/EQpVSEiMcBGEdnbTdm+7ld39Pe88chAo5Sa\nfR7VutMQ78xei+301lf/stuXP9tWuYj4Alag7jz6OIfe+iYiLwEfuolv/YGr+z8HpVSF/qwWkfew\nXd5ViUi8UqpSX/5U6+Jdjb8cmNnBvlnbEzspTzd9uC+uniRy1sa5k8GjaT+ZuR/bBKOvTg+hbZJx\ntK7zFu0nTH+h07+k/YTp2vPto48+xdull2ObM3Gpb/14PB2yDx04nhAgzC69HbgGeIr2E7VP6vS/\n0H4yOEvbI4EybBPBETodqfOyddmzk8Fztb3TPtx5c/kAnPAP8FNsvwZNQBWwwS7vYWx3LorQM/ja\nPhfYp/MetrOnYJv5L9FfzABtD9R/l+j8lPPto4++/RXIA3YDGR0Cj8t868dje8H70IFjSdHBLhfY\nc3Y82OazNgHF+vNs0BDgOT32PNr/CC7V+7sE+JmdPR3I13Wepe1J/k77cOfNvIJgMBiczo/prpPB\nYHARJtAYDAanYwKNwWBwOibQGAwGp2MCjcFgcDom0BgMBqdjAo3BYHA6/w8k/dV1XgG8agAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "protected_areas_border.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [],
   "source": [
    "data_within_border = geopandas.sjoin(data_utm, protected_areas_border,\n",
    "                                     op='within', how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "clear_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Kahuzi-Biega National park      99\n",
       "Okapi Faunal Reserve            50\n",
       "Maiko National park             33\n",
       "Itombwe Nature Reserve          32\n",
       "Luama-Kivu Hunting Domain       23\n",
       "Kisimba Ikobo Nature Reserve    21\n",
       "Tayna Nature Reserve            11\n",
       "Luama-Katanga Hunting Domain     9\n",
       "Upemba National park             4\n",
       "Virunga National park            3\n",
       "Mulumbu Hunting Domain           1\n",
       "Name: NAME_AP, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_within_border['NAME_AP'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Extracting information from raster layer\n",
    "\n",
    "This section shows an example how to extract information from a raster layer for each of the vector features. In this case, we will extract the value of a vegetation map for each mining site. The data can be downloaded from http://www.wri.org/our-work/project/congo-basin-forests/democratic-republic-congo#project-tabs (scroll a bit down, and in the right sidebar you can download the \"Vegetation\" data).\n",
    "\n",
    "We use the [`rasterstats`](https://github.com/perrygeo/python-rasterstats) package to do this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rasterstats import point_query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "vegetation_raster = \"data/Vegetation/Carte_vgt_ucl_10/carte_foraf/central_africa_vegetation_map_foraf.tif\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/joris/miniconda3/lib/python3.5/site-packages/rasterstats/point.py:167: FutureWarning: The value of this property will change in version 1.0. Please see https://github.com/mapbox/rasterio/issues/86 for details.\n",
      "  with Raster(raster, nodata=nodata, affine=affine, band=band) as rast:\n",
      "/home/joris/miniconda3/lib/python3.5/site-packages/rasterstats/io.py:242: FutureWarning: GDAL-style transforms are deprecated and will not be supported in Rasterio 1.0.\n",
      "  self.affine = guard_transform(self.src.transform)\n",
      "/home/joris/miniconda3/lib/python3.5/site-packages/rasterstats/io.py:294: UserWarning: Setting nodata to -999; specify nodata explicitly\n",
      "  warnings.warn(\"Setting nodata to -999; specify nodata explicitly\")\n"
     ]
    }
   ],
   "source": [
    "data['vegetation'] = point_query(data.geometry, vegetation_raster, interpolate='nearest')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The legend available as an excel file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend = pd.read_excel(\"data/Vegetation/Carte_vgt_ucl_10/carte_foraf/legend_central_africa_vegetation_map_foraf.xls\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['vegetation'] = data['vegetation'].replace(legend['Final Label (sur le tif)'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2141    Mosaic cultivated areas / vegetation (herbaceo...\n",
       "2142    Mosaic cultivated areas / vegetation (herbaceo...\n",
       "2143            Rural complex and Young secondary forest \n",
       "2144                      Savanna woodland - Tree savanna\n",
       "2145            Rural complex and Young secondary forest \n",
       "2146            Rural complex and Young secondary forest \n",
       "2147                                    Submontane forest\n",
       "2148            Rural complex and Young secondary forest \n",
       "2149            Rural complex and Young secondary forest \n",
       "2150            Rural complex and Young secondary forest \n",
       "Name: vegetation, dtype: object"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['vegetation'].tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7faebd571320>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7vaz6Zi47lv9MXLcUTr76JsKjo8k7lMncfzxJ9p5dWKYZcDV9eHQMt7/4JnqAmXjrvv+G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\n2etGbDTH8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4DPS+GurCbHhKKgas4W6qBgKYRWlRz6zGWbIxvbAHQFVfnwzHRL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\nAEVRzimrNIv0wnRMaZ57Y6XBUJPBKYpSqcySTB5e/jD7C/ajCY1IWyTPj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wwAACAASURB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jNTzMGMtx05ViMaCYFMR2pQOwidPko1z+bhVxEYP28q940ggighTYEce15TB0dCoaFaYDAKcc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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(column='vegetation', figsize=(15, 15), legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
